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

Merck (MSD)
Location
USA - Pennsylvania - West Point
Job Type
Full-time
Posted
October 1, 2026
Views
10
Salary Range
$82k - $92k USD

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.

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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.

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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Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.  As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities.  For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

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We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.

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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company.  No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Employee Status

Regular

Relocation

Domestic

VISA Sponsorship

Yes

Travel Requirements

10%

Flexible Work Arrangements

Not Applicable

Shift

Not Indicated

Valid Driving License

No

Hazardous Material(s)

N/A

Job Posting End Date

10/12/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.

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Frequently Asked Questions

Where is the job located, and is it remote/hybrid/on-site?
The position is located on-site in West Point, Pennsylvania, USA.
What are the required qualifications and experience level?
Candidates must hold a PhD, or receive one by spring 2027, in Computational Biology, Bioinformatics, Computer Science, Biophysics, Computational Chemistry, or a related quantitative discipline. Required skills include AI/ML expertise with biomolecular data, Python and ML framework proficiency, and a proven publication track record.
What are the key responsibilities of this role?
You will develop and deploy novel AI/ML architectures for antigen design, integrate physics and machine learning (such as MD simulations), interface with high-throughput experimental screening platforms to refine models, author scientific manuscripts, and collaborate across structural biology, virology, and immunology teams.
What is the salary range for this position?
The salary range for this role is $82,000 to $92,000. The successful candidate may also be eligible for an annual bonus and long-term incentives.
Is visa sponsorship or relocation support available?
Yes, visa sponsorship is available for this position, and domestic relocation support is also provided.
What benefits does the company offer?
Benefits include medical, dental, and vision healthcare (for employee and family), retirement benefits including a 401(k), paid holidays, vacation, compassionate and sick days, dedicated compute and cloud resources, and targeted career development.
What is the application deadline for this position?
The job posting end date is 10/12/2026. You must apply no later than the day before this date (by 11:59:59 PM on 10/11/2026).

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Job Information

Source: manual
AI Relevance: 95/100 (Highly relevant)
Remote Type: onsite
Allowed Locations: Worldwide
Skills & Tags:
merck (msd) machine learning deep learning artificial intelligence bioinformatics computational biology data science protein structural biology immunology

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