Associate Scientist, Post Doc Fellow- AI/ML & Computational Biology for Antigen Design

Location: USA - Pennsylvania - West Point

Job Description

Postdoctoral Fellow – AI/ML & Computational Biology for Antigen Design

Location: West Point, PA (On-site)

Department: Infectious Diseases & Vaccines Discovery / Data Science & Scientific Informatics

Position Overview:

We are seeking an exceptional and motivated Postdoctoral Scientist to join our interdisciplinary team at the forefront of computational vaccine discovery. In this role, you will pioneer and apply state-of-the-art artificial intelligence (AI), machine learning (ML), and computational protein design techniques to solve fundamental challenges in structure-based antigen design.

Many viral pathogens present dynamic, conformationally flexible surface proteins that require precise structural stabilization to elicit potent protective immune responses. You will spearhead the development of predictive AI/ML workflows to model, design, and optimize conformationally constrained viral antigens. Working closely with both computational biologists and high-throughput experimental screening groups, you will operate in a tight computational-experimental feedback loop to iteratively fine-tune generative models with empirical datasets.

As an industry postdoctoral fellow, you will be dedicated to high-impact discovery research with the freedom and expectation to collaborate with scientists across our company, present data at major international conferences, and publish findings in leading peer-reviewed journals.

Key Responsibilities:

Algorithm & Workflow Development: Develop, benchmark, and deploy novel AI/ML architectures including protein language models, folding models, geometric deep learning models, and inverse-folding models for variant prediction and conformational stabilization.

Physics & Machine Learning Integration: Explore hybrid computational strategies integrating molecular dynamics (MD) simulations, energetic modeling, and deep learning representations to capture dynamic conformational transitions.

Data-Driven Iteration: Interface with high-throughput automated expression, biophysical characterization, and analytical screening platforms to iteratively benchmark, retrain, and refine candidate models using prospective experimental data.

Scientific Dissemination: Author high-impact manuscripts, present findings at prestigious computational biology and vaccine development symposiums, and champion open science practices within industry boundaries.

Cross-Functional Collaboration: Partner with subject-matter experts across structural biology, virology, immunology, and research computing to translate computational breakthroughs into translatable vaccine designs.

Education Requirements:

Must currently hold a PhD OR

Receive a Ph.D. no later than spring 2027

Ph.D. in Computational Biology, Bioinformatics, Computer Science, Biophysics, Computational Chemistry, or a related quantitative discipline.

Required Experience and Skills:

AI & Machine Learning Expertise: Demonstrated experience developing or applying machine learning models to biomolecular data, with practical fluency in protein language models (e.g., ESM), folding models (e.g., AlphaFold), or structural inverse-folding (e.g., ProteinMPNN) paradigms.

Computational Fluency: Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX), alongside experience in high-performance computing (HPC), GPU workflows, version control, and reproducible software development.

Publication Track Record: Proven record of independent research demonstrated through first-author peer-reviewed publications, preprints, or presentations at major conferences.

Preferred Experience and Skills:

Experience with structural modeling suites (e.g., ColabFold, Rosetta, PyMOL/ChimeraX) and molecular dynamics tools (e.g., AMBER, Desmond, GROMACS, OpenMM).

Working knowledge of biophysical and biochemical characterization methods (e.g., thermal stability/nanoDSF, binding kinetics/SPR/BLI, SEC) and how experimental data informs model training.

Experience with dynamic or oligomeric protein complexes which undergo conformational rearrangements.

Strong written and verbal communication skills with an appetite for working in multidisciplinary, team-oriented environments.

Program Benefits & Culture:

Our Postdoctoral Program offers an immersive, academic-style research environment embedded within a world-class biopharmaceutical enterprise. Fellows receive dedicated mentorship, competitive compensation and comprehensive benefits, dedicated compute and cloud resources, and targeted career development designed to prepare researchers for leading careers in either academia or the biotechnology industry.

The salary range for this role is: $82,000- $92,000

This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to relevant education, qualifications, certifications, experience, skills, geographic location, government requirements, and business or organizational needs.

The successful candidate will be eligible for annual bonus and long-term incentive, if applicable.

We offer a comprehensive package of benefits. Available benefits include medical, dental, vision healthcare and other insurance benefits (for employee and family), retirement benefits, including 401(k), paid holidays, vacation, and compassionate and sick days.

Required Skills: Bioinformatic Analysis, Computational Biology, Data Analysis, Immunology Research, Molecular Dynamics (MD), Programming Languages, Protein Design, Protein Structure Prediction, Statistical Analysis, Structural Biology, Vaccine Development

Preferred Skills:

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US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabili