Post Doc Fellow-Immunogenicity Prediction

Job Description The Computational Toxicology group within Nonclinical Drug Safety (NDS) seeks a Postdoctoral Fellow to advance AI/ML and structure-based approaches for immunogenicity prediction in biologic and peptide therapeutics. The successful candidate will develop next-generation computational methods combining protein structure modeling, immunoinformatics, and multimodal machine learning to improve prediction of biologically relevant immune responses. This is a publication-oriented, two-year fellowship with strong mentorship and extensive cross-functional and external academic collaboration. The Fellow will publish first-author manuscripts, present at scientific conferences, and help establish reusable, well-documented computational capabilities for translational safety assessment. Key responsibilities Curate, integrate, and harmonize biological, structural, and clinical datasets from public and internal sources into reproducible analysis workflows. Develop computational methods for immunogenicity prediction by integrating sequence, structural, and experimental data. Apply structure-based modeling and simulation approaches to characterize biomolecular interactions and conformational behavior relevant to immune recognition. Build and benchmark multimodal machine-learning models that combine sequence, structural, and tabular data into robust, calibrated predictors. Evaluate model performance against established approaches and assess generalizability across therapeutic modalities. Contribute to first-author manuscripts and scientific presentations at internal forums and external conferences. Collaborate with computational, biology, and experimental scientists, and deliver reproducible, well-documented code, analyses, and models. Educational Requirements Must currently hold a PhD OR Receive a Ph.D. no later than spring 2027 Ph.D. in computational immunology, computational biology, computational chemistry, structural biology, bioinformatics, or a closely related field. Required Experience and Skills Strong hands-on experience with co-folding models (e.g AlphaFold2/Boltz2), multimer modeling, or related structure-based computational methods. Experience with molecular dynamics simulation and analysis of biomolecular systems, complexes, or conformational behavior. Strong software development skills in Python and modern deep-learning frameworks such as PyTorch, with sound practices in version control, reproducibility, and scientific computing. Working knowledge of immunology relevant to immunogenicity prediction, including antigen processing and presentation, MHC / HLA biology, CD4⁺ T-cell recognition, and anti-drug antibody (ADA) responses. Comfort working in HPC / GPU and cloud computing environments. Excellent scientific communication skills and a strong first-author publication record. Preferred Experience and Skills Experience applying computational methods to immunology, structural biology, or protein science problems. Familiarity with antigen processing and presentation, MHC/HLA biology, or related immune recognition concepts. Experience with data integration, biological dataset curation, and programmatic workflows using public resources and APIs. Familiarity with uncertainty quantification, model calibration, and rigorous benchmarking. Familiarity with biotherapeutic developability, protein engineering, or related optimization concepts. Exposure to immunoinformatics, peptide modeling, or related predictive methods is a plus. 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 Biological Data Analysis, Biology, Biomolecular Interactions, Computational Biology, Immunology Research, Machine Learning, Programming Languages, Protein Analysis, Protein Interactions, Scientific Presentations Preferred Skills Current Employees apply HERE ( Current Contingent Workers apply HERE ( 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 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. 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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. Requisition ID: R419989 #J-18808-Ljbffr Merck