Get the chrome extension Data Science Fellow — Organoid Biochemistry
Axle
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
-
Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
Position Overview
The Postdoctoral Fellow will help establish the laboratory’s core capacity for protein-focused biological support, connecting organoid phenotype and optical measurements to molecular mechanisms. The Fellow will implement two complementary platforms: Amplicon/Protein Bead Display (APB-Display) for rapid production, screening, and quantitative characterization of protein or nanobody libraries; and SMA/SMALP or related membrane-active-polymer workflows for detergent-free extraction of membrane proteins and associated lipids into native nanodiscs. The position serves as the principal biochemical resource for the two existing optical-methods postdocs and works closely with the chemical-spectroscopy postdoc on toxicant-induced changes in proteins, membranes, and lipid environments. The appointment is intended to prepare the Fellow for an independent research career in academia, government, or industry.
Key Responsibilities
Biochemical support. Establish routine molecular-biology, protein-expression, purification, conjugation, and biochemical-assay support for organoid projects, including recombinant protein and nanobody production in bacterial, yeast, cell-free, or mammalian systems as appropriate.
APB-Display implementation. Implement APB-Display using dual-functional hydrogel beads, pooled DNA libraries, particle-templated emulsification, emulsion PCR, emulsion in-vitro transcription/translation, SNAP-mediated protein capture, fluorescence-based expression and binding measurements, FACS sorting, and sequencing-based readout.
Library design. Develop focused nanobody and affinity-reagent libraries informed by in-silico design, biological targets, chemical-toxicity hypotheses, and needs identified by the imaging and spectroscopy researchers.
Quantitative screening. Implement APB-SortSeq for rapid single-concentration screening and APB-TiteSeq for quantitative concentration-series measurements of expression and binding affinity; establish controls for genotype-phenotype linkage, nonspecific binding, ligand depletion, bead occupancy, and sequencing representation.
Orthogonal validation. Validate selected binders and interaction measurements with orthogonal methods such as fluorescence polarization, ELISA, pull-down/immunoprecipitation, biolayer interferometry, surface plasmon resonance, size-exclusion chromatography, or other accessible assays.
Membrane-polymer workflows. Establish SMA/SMALP and related membrane-active-polymer screening in relevant cell lines, organoid-derived cells, tissue preparations, and organoid models. Use fluorescence-based bulk-solubilization assays, polymer and buffer optimization, and target-protein-specific recovery measurements to select conditions that preserve native protein-lipid assemblies.
Nanodisc quality control. Apply quality-control methods for native nanodiscs, including fluorescence measurements, dynamic light scattering, size-exclusion chromatography, negative-stain electron microscopy through a core facility, gel-based analysis, and mass-spectrometry-compatible preparation.
Membrane-complex enrichment. Coordinate targeted extraction and affinity enrichment of membrane proteins and complexes from plasma membrane, mitochondria, endoplasmic reticulum, Golgi, lysosomal, or other organellar membranes; preserve samples for proteomic, lipidomic, functional, structural, and electron-tomography follow-up.
Nanobody-enabled workflows. Develop nanobody-enabled labeling, concentration, purification, and perturbation workflows for organoid imaging, membrane-complex analysis, and potential countermeasure applications.
Documentation and cross-training. Create version-controlled SOPs, reagent inventories, assay acceptance criteria, sample metadata, and training modules; cross-train other team members in routine biochemical procedures and troubleshoot biologically driven variation in imaging or spectroscopy studies.
Required Qualifications
Education. Doctoral degree (PhD) in biochemistry, molecular biology, chemical biology, protein chemistry, biophysics, bioengineering, cell biology, or a closely related field.
Laboratory experience. Demonstrated hands-on experience in recombinant protein expression and purification, molecular cloning, quantitative binding assays, or protein-interaction analysis.
Scientific foundation. Strong understanding of protein structure-function relationships, membrane biology, assay controls, and quantitative experimental design.
Collaboration. Ability to work with mammalian cells or complex biological samples and to collaborate with imaging, spectroscopy, toxicology, computational, and core-facility teams.
Documentation and analysis. Ability to document methods rigorously, analyze data using Python, R, MATLAB, or comparable tools, and communicate results through reports, presentations, and manuscripts.
Preferred Qualifications
Experience with nanobodies, antibody engineering, display technologies, pooled libraries, FACS, next-generation sequencing, cell-free protein synthesis, microfluidics, or hydrogel beads.
Experience with styrene-maleic-acid polymers, SMALPs, native nanodiscs, membrane-protein purification, lipidomics, quantitative proteomics, mass spectrometry, or electron microscopy sample preparation.
Experience with organoids, stem-cell-derived models, toxicology, chemical exposures, fluorescence imaging, or multi-omics integration.
A strong record of method development, troubleshooting, collaborative publications, and independent experimental execution.
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Data Scientist Fellow — AI/ML
Axle
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
-
Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
Position Overview
The Data Scientist Fellow will develop computational models to predict and optimize organoid growth and differentiation protocols in support of the SOM Center. The incumbent will apply advanced machine learning techniques to organoid standardization and contribute to the development of predictive models for tissue engineering applications.
Key Responsibilities
Model development. Design and implement machine learning models that predict organoid development outcomes based on protocol parameters, environmental conditions, and molecular characterization data.
In silico simulation. Develop in silico models that correspond to organoid growth, maturation, and characterize phenotype while identifying optimal conditions for reproducible organoid generation.
Feedback systems. Establish feedback loops between experimental validation and computational prediction in order to iteratively refine and understand protocol standardization.
Interdisciplinary collaboration. Work with experimental teams to design characterization and validation experiments and with bioinformatics scientists to integrate multi-modal datasets.
Required Qualifications
Education. Doctoral degree (PhD) in computer science, engineering, applied mathematics, or a related field, with demonstrated experience in AI/ML model development.
Programming. Strong programming proficiency in Python, R, or comparable languages, together with experience using machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.
Applied experience. Prior experience applying computational methods in biological laboratory settings, including working knowledge of experimental design principles and biological data types.
Preferred Qualifications
Experience with organoid systems or tissue engineering applications.
Knowledge of differential equations and systems biology modeling, and experience with deep learning approaches for biological applications.
Familiarity with cloud computing platforms and containerization technologies.
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Data Scientist Fellow, Bioinformatics and Image Analysis
Axle
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
-
Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
Position Overview
The Postdoctoral Fellow will turn the data produced by the autonomous laboratory in Bethesda into results that the lab can act on. The platform runs biological experiments on the BAB400 robot, which comes with a Cytation 9 imaging system, and the main data stream is microscopy images. The Fellow will build and run the image analysis and bioinformatics pipelines that measure what happened in each experiment, combine those measurements with environmental monitoring data collected alongside the experiments, and return quantitative readouts to the autonomous loop so that it can decide what to run next. The Fellow will work side by side with the Laboratory Automation Engineer and with the biologists and data engineers of IDSS. This is a hybrid research position: the Fellow is expected to contribute new methods, publish, and present, in addition to keeping the analysis running reliably.
Key Responsibilities
Image analysis pipelines. Develop and maintain automated pipelines for Cytation 9 images, including quality control, illumination and background correction, segmentation, tracking, and feature extraction for cultures such as iPSC colonies and, later, organoids.
Quantitative readouts for the loop. Define and validate metrics that describe culture state and growth (for example confluence, colony morphology, differentiation markers, and viability), with uncertainty estimates, so that they can be used as decision inputs by the autonomous system.
Closing the loop. Work with the Laboratory Automation Engineer to deliver analysis results back to the workflow orchestration layer in a machine-readable form and on a timescale the loop can use. Define the interfaces, the failure behavior, and the checks that stop bad data from driving a bad decision.
Environmental data integration. Collect, clean, and align environmental monitoring data (for example temperature, CO2, O2, humidity, and other sensor streams) with imaging results. Analyze how conditions relate to culture outcomes and flag drift, excursions, and sensor faults.
Statistical and machine learning methods. Apply and develop statistical, machine learning, and deep learning methods for image and multimodal data, with attention to validation, reproducibility, and batch effects. Use the existing Cytation and instrument software where it helps, and build custom methods where it does not.
Bioinformatics. Integrate downstream omics data, including single-cell data, generated from the experiments where they are available, and link them to image-derived phenotypes.
Data management. Work with IDSS data engineers so that images, derived measurements, and metadata are stored, versioned, and findable in line with FAIR principles and NIH data management and sharing requirements.
Research and communication. Publish methods and results, present to NIAID and collaborators, document pipelines and standard operating procedures, and train staff to use the analysis tools.
Required Qualifications
Education. Doctoral degree (PhD or equivalent) in bioinformatics, computational biology, biomedical engineering, computer science, physics, or a related quantitative field, normally completed within the last five years.
Image analysis. Demonstrated experience analyzing microscopy or other biological image data, including segmentation and quantitative feature extraction.
Programming. Strong Python, including scientific and imaging libraries (NumPy, SciPy, pandas, scikit-image, or similar) and at least one machine learning framework (PyTorch, TensorFlow, or similar).
Statistics and experimental design. Strong grounding in statistics and experimental design, and experience validating analysis methods.
Reproducible practice. Experience with Git and reproducible analysis practices, and with working in a Linux or high-performance computing environment.
Research record. A record of research output, such as peer-reviewed publications, preprints, or released software.
Collaboration. Ability to work in a close, iterative partnership with an automation engineer and biologists, and to explain methods and results clearly to both.
Clearance. Ability to obtain and maintain NIH/HHS security clearance and meet federal contractor suitability requirements.
Preferred Qualifications
Experience with high-content or live-cell imaging systems, especially Agilent BioTek Cytation or Gen5 software.
Experience with image analysis tools such as CellProfiler, Cellpose, StarDist, napari, or ImageJ/Fiji, and with deep learning methods for segmentation and classification.
Experience with stem cell, iPSC, organoid, or tissue culture systems and their imaging.
Experience with time-series or multimodal analysis, including sensor and environmental monitoring data.
Experience with self-driving laboratories, active learning, or Bayesian optimization.
Experience with single-cell omics analysis (scRNA-seq) and with workflow tools such as Nextflow or Snakemake.
Familiarity with laboratory orchestration software such as MADSci, and with Docker or Kubernetes.
Experience with high-performance computing environments (for example NIH Biowulf).
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Data Scientist Fellow — Multi-Omics Analysis
Axle
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
-
Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
Position Overview
The Bioinformatics Fellow for Multi-Omics Analysis will conduct comprehensive analyses of multi-omics data generated from organoid systems and corresponding normal tissues. The incumbent will characterize organoid fidelity, identify biomarkers of successful differentiation, and develop computational frameworks for organoid quality assessment, while gaining substantive training in integrative analysis of single-cell and multi-omics data. The work is central to the SOM Center’s research objectives, and the position is intended to prepare the Fellow for an independent research career in academia, government, or industry.
Key Responsibilities
Multi-omics analysis. Analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from a range of organoid systems and their tissue counterparts.
Pipeline development. Develop and implement computational pipelines for data processing, quality control, and statistical analysis, and document them so that analyses are reproducible across the Center.
Benchmarking. Integrate SOM-generated data with publicly available datasets in order to benchmark organoid characteristics against normal tissue profiles.
Method development. Develop and refine analytical approaches — including machine learning methods where appropriate — for classifying cellular states and assessing organoid quality, and contribute to standardized assessment protocols.
Collaboration and interpretation. Work closely with experimental teams to interpret results and guide protocol optimization, and collaborate with other computational staff on cross-modality data integration.
Dissemination. Contribute to manuscript preparation and present findings at scientific conferences.
Required Qualifications
Education. Doctoral degree (PhD) in bioinformatics, computational biology, biostatistics, or a related quantitative field, completed or anticipated prior to the start of the appointment.
Single-cell analysis. Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or comparable platforms.
Programming. Strong programming proficiency in R and Python, together with experience in statistical analysis and data visualization.
Omics workflows. Working knowledge of proteomics and metabolomics data analysis workflows.
Preferred Qualifications
Prior experience analyzing organoid datasets.
Experience with machine learning approaches for biological data, familiarity with pathway analysis tools, and knowledge of developmental biology principles.
Experience with high-performance computing environments and version control systems.
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Laboratory Automation Engineer (Robotics and Digital Twins)
Axle
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
-
Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
Position Overview
The Laboratory Automation Engineer will program, integrate, and keep running the robots of the autonomous laboratory in Bethesda, starting with the BAB400, so that biological experiments run reliably without a person at the bench. The role builds the software layer that turns robot hardware into orchestrated, repeatable workflows, using the MADSci framework from Argonne National Laboratory. It also builds digital twins of the robots and workcells, used to plan, test, and validate protocols before they run on real hardware. The position combines hands-on robotics work in a biological lab with production-quality software development, and it works closely with IDSS data engineers, bioinformaticians, and the biologists who define the protocols.
Key Responsibilities
Robot programming and control. Program, calibrate, and maintain the BAB400 and other laboratory robots, including arms, liquid handlers, plate movers, and incubator and imaging interfaces.
MADSci integration. Deploy MADSci modules, nodes, and workcell definitions so each robot and instrument can be commanded, monitored, and scheduled through a common interface. Contribute fixes and new modules back to the framework where appropriate.
Workflow development and scheduling. Translate biological protocols (cell culture, iPSC maintenance, passaging, media exchange, imaging, sampling) into automated workflows with sequencing, timing, resource tracking, and recovery from failures.
Instrument and data integration. Connect robot and instrument outputs to the data pipelines, LIMS, and metadata systems maintained by IDSS, so every run is logged, traceable, and reusable.
Validation and reliability. Develop acceptance tests, error handling, logging, and monitoring. Troubleshoot hardware and software faults, and document root causes and fixes.
Safety and compliance. Implement interlocks and safe-state behavior, and follow laboratory, biosafety, and NIH/HHS security requirements.
Tool evaluation. Evaluate robots, drivers, simulators, and frameworks, and prepare short technical assessments for IDSS leadership.
Training and documentation. Train laboratory staff to operate and recover the system, and write standard operating procedures and technical documentation.
Required Qualifications
The selection standard is demonstrated ability to get automated systems working. A degree in engineering, computer science, robotics, or a related science is common, but equivalent practical experience is fully acceptable.
Automation experience. Several years of hands-on experience with laboratory robotics or comparable automation, such as robotic arms, liquid handlers, plate handlers, or workcells, including installing, programming, calibrating, and troubleshooting them.
Robot software. Experience with the software that drives laboratory robots: vendor APIs and SDKs, device drivers, and orchestration or scheduling software.
Laboratory context. Some experience with robotics in a biological laboratory (cell culture, molecular biology, or assay automation), and comfort working around biological materials under biosafety practices.
Programming. Strong Python, including asynchronous or service-style code, REST APIs, and working with hardware or network protocols (serial, TCP/IP, OPC UA, or similar).
Software engineering practices. Experience with Git, testing, and code review, and with Docker for deploying software next to hardware.
Protocol translation. Ability to read a protocol, understand what the biology requires, and turn it into a reliable automated workflow.
Communication. Strong communication skills and the ability to train laboratory staff.
Clearance. Ability to obtain and maintain NIH/HHS security clearance and meet federal contractor suitability requirements.
Preferred Qualifications
Direct experience with MADSci, or with similar laboratory orchestration frameworks (for example PyLabRobot, Opentrons tooling, or ROS-based systems).
Experience with simulation platforms such as NVIDIA Isaac Sim, Gazebo, MoveIt, or similar robot simulators.
Experience with stem cell, iPSC, organoid, or tissue engineering laboratories.
Experience with self-driving or autonomous laboratories, including closed-loop experiments driven by ML or optimization.
Familiarity with ROS 2, robot kinematics, and computer vision for labware or sample detection.
Experience with Kubernetes, CI/CD, and message-based architectures (MQTT, Redis, or similar).
Familiarity with LIMS, ELN, and metadata standards, and with FAIR data principles.
Experience with imaging instruments and plate-based assays.
Experience building or using simulation or digital-twin models of robotic systems, or a clear record of learning a new simulator quickly.
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Research Data Manager
Axle
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
-
Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
Position Overview
The Research Data Manager will build and maintain the data infrastructure for the SOM Center. This includes the Laboratory Information Management System (LIMS), document and repository platforms such as Invenio, and the metadata databases and pipelines that connect them. The role brings together instrument, assay, and analysis data and makes it findable, traceable, and reusable, in line with NIH data management and sharing requirements. The position combines hands-on software development with data stewardship, using cloud-native tooling and AI/ML to make data easier to find and use.
Key Responsibilities
Data integration. Connect laboratory instruments, analysis pipelines, and external data sources to the LIMS. Build and maintain automated ingestion pipelines with validation, logging, and error handling.
Data wrangling and format conversion. Write and maintain custom scripts and services that convert, normalize, and harmonize heterogeneous data formats (instrument exports, imaging metadata, omics outputs, spreadsheets) into standardized schemas.
Repository and document management. Deploy, configure, and support document and research data management systems such as Invenio. Manage records, metadata schemas, persistent identifiers, and access controls.
Database development. Design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, and backup and recovery.
AI/ML-assisted discovery. Incorporate ML/AI into data workflows and user interfaces, such as semantic search, metadata extraction and auto-annotation, and natural-language query tools, to help researchers find and use data.
Platform and cloud engineering. Develop, containerize, and deploy software solutions on cloud or local Kubernetes resources. Maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
Tool evaluation. Evaluate and recommend packages, platforms, and standards for data management, and prepare short technical assessments for IDSS leadership.
Training and documentation. Train laboratory and analytical staff, and write standard operating procedures and technical documentation.
Required Qualifications
Data integration. Connect laboratory instruments, analysis pipelines, and external data sources to the LIMS. Build and maintain automated ingestion pipelines with validation, logging, and error handling.
Data wrangling and format conversion. Write and maintain custom scripts and services that convert, normalize, and harmonize heterogeneous data formats (instrument exports, imaging metadata, omics outputs, spreadsheets) into standardized schemas.
Repository and document management. Deploy, configure, and support document and research data management systems such as Invenio. Manage records, metadata schemas, persistent identifiers, and access controls.
Database development. Design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, and backup and recovery.
AI/ML-assisted discovery. Incorporate ML/AI into data workflows and user interfaces, such as semantic search, metadata extraction and auto-annotation, and natural-language query tools, to help researchers find and use data.
Platform and cloud engineering. Develop, containerize, and deploy software solutions on cloud or local Kubernetes resources. Maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
Tool evaluation. Evaluate and recommend packages, platforms, and standards for data management, and prepare short technical assessments for IDSS leadership.
Training and documentation. Train laboratory and analytical staff, and write standard operating procedures and technical documentation.
Preferred Qualifications
Experience deploying or customizing Invenio/InvenioRDM or similar repositories (Dataverse, DSpace, CKAN).
Experience integrating ML/AI components into applications, such as embeddings and vector search, LLM-based retrieval, or document parsing.
Familiarity with workflow tools (Airflow, Nextflow, Snakemake, Argo) and with Helm, Terraform, or similar infrastructure-as-code tools.
Experience with stem cell or tissue engineering laboratories.
Experience with imaging and omics data.
Experience with high-performance computing environments (for example NIH Biowulf).
Experience with front-end tooling (React or similar) for data-facing interfaces.
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.
Laboratory Technician
Axle
(ID: 2026-3842)
Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH).
Axle is seeking a Laboratory Technician to join our vibrant team at the National Institutes of Health (NIH) supporting the National Heart, Lung, and Blood Institute (NHLBI) located in Bethesda, MD.
Benefits We Offer:
- 100% Medical, Dental & Vision Coverage for Employees
- Paid Time Off and Paid Holidays
- 401K match up to 5%
- Educational Benefits for Career Growth
- Employee Referral Bonus
- Flexible Spending Accounts:
- Healthcare (FSA)
- Parking Reimbursement Account (PRK)
- Dependent Care Assistant Program (DCAP)
- Transportation Reimbursement Account (TRN)
Position Information:
The purpose of this contract is to perform laboratory procedures (human sample handling and processing, extraction and quantitation of nucleic acids and proteins) and assays (molecular biology assays such as gel electrophoresis, enzymatic assays, PCR, etc.), under the direction [of] the principal investigator and senior scientists, which are core experimental research activities.
Additional Qualifications:
Certifications & Licenses
-
Associates degree with at least four (4) years of experience or Bachelor’s with at least two (2) years of experience in molecular biology or a related field is required
Field of Study
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Molecular Biology
Software
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Experience with MS Word, Excel, Access, and GraphPad Prism.
Skills
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Knowledge of proper laboratory disposal methods and safety procedures.
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Must be organized with a strong ability to multi-task, prioritize, and be attentive to detail.
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Must possess a high level of independent judgment and accuracy.
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Strong interpersonal skills and an ability to establish and maintain effective working relationships with colleagues.
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Excellent oral and written communication skills.
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Ability to work independently and reliably.
Deliverables:
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Work products and documents related to maintaining and completing laboratory logs; manage inventory and procure laboratory supplies, reagents and equipment; perform laboratory procedures. - Daily
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Work products and documents related to assessing and utilizing methods and/or procedures for use in laboratory experiments; make modifications and improvements in laboratory methods/procedures to meet specific needs or experimental situations. - Weekly
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Work products and documents related to maintenance of patient sample inventory and database and extraction and quantitation of nucleic acids and proteins from patient samples; procure and maintain inventory of laboratory supplies, including required documentation. - Weekly
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Work products and documents related to laboratory safety compliance, institution’s rules and regulations, such as institutional review board protocols, environmental health and safety, and waste management. - Monthly
Statement of Work Details:
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Experience with molecular biological techniques, including, but not limited to pipetting, centrifugation, buffer preparation; DNA/RNA isolation and quantification; primer/probe design ;PCR; RT-PCR; qPCR and gel electrophoresis, imaging and purification. - 1
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Perform laboratory procedures (human sample handling and processing, extraction and quantitation of nucleic acids and proteins) and assays (molecular biology assays such as gel electrophoresis, enzymatic assays, PCR, etc.), under the direction the principal investigator and senior scientists. - 2
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Responsible for sample shipping, receiving, storage, and inventory. Shall also aid in monitoring and updating the NIH Sickle Cell Branch inventory repository. - 3
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Maintain log of laboratory safety compliance; ensure that regulations are being followed. - 4
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Provides technical experience needed to assist in studying the basic principles of plant and animal life.
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Make recommendations to effectively resolve issues by using judgment that is consistent with standards, practices, policies, procedures, and regulations or law.
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Assists with performing basic laboratory experiments and procedures.
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Collect and analyze biological data about relationships among and between organisms and their environment.
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Monitor and observe experiments, recording production and test data for evaluation by research personnel.
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Assist in developing novel assays and methodologies as needed for the planned fundamental and translational research.
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Prepares, organizes and maintains various lab samples, supplies, and equipment.
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Maintain laboratory equipment.
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Analyze laboratory findings.
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Prepare reports and present data to supervisors, lab members, and collaborators.
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Generate protocols and updates.
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Maintain and accurately complete laboratory logs (patient samples -whole blood, plasma, DNA, RNA, Protein).
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Maintain inventory and procure laboratory supplies, reagents, and equipment when needed.
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Learns new laboratory techniques and procedures.
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Program and use computers to store, process, and analyze data.
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Monitor operational procedures in technical environments to ensure conformance to standards.
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Record research or operational data.
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Make modifications and improvements in laboratory methods/procedures, in collaboration with lab personnel, to meet specific needs or experimental situations.
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Comply with institution’s rules and regulations, such as institutional review board protocols, environmental health and safety, and waste management.
Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed.
The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate.
Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com
This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location.