Data Science Fellow
Axle
Data Science Fellow
Axle
Translational research informatics and data science
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:
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: [email protected]
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.
Salary Range 90000 - 100000 USD
Axle Informatics provides specialized informatics solutions for translational research, health informatics, and data science to biomedical research centers and healthcare organizations. It offers customized software and data management platforms that help researchers collect, integrate, analyze, and visualize large research datasets. The company combines biomedical science, software engineering, and program management to automate data aggregation and deliver analytics, dashboards, and decision-support tools that bridge lab findings to clinical applications. Its goal is to advance public health by accelerating the translation of biomedical discoveries into real-world treatments and diagnostics, improving healthcare outcomes.
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