Post Doc Fellow-Immunogenicity Prediction

HireLifeScience

West Point (PA)

On-site

USD 82,000 - 92,000

Full time

2 days ago

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Benefits offered by this job

Annual bonus

Long-term incentive

Medical, dental, vision benefits

Job summary

HireLifeScience is seeking a Postdoctoral Fellow in the Computational Toxicology group within Nonclinical Drug Safety to advance AI/ML and structure-based approaches for immunogenicity prediction in biologic and peptide therapeutics. The role emphasizes publication, collaboration, and development of reusable computational capabilities for translational safety assessment.

The fellow will curate diverse datasets, develop integrated predictive models, publish first-author papers, present findings

Qualifications

Must hold a PhD OR
Ph.D. no later than spring 2027
Ph.D. in computational immunology, computational biology, computational chemistry, structural biology, bioinformatics, or a closely related field.

Responsibilities

Curate and harmonize biological, structural, and clinical data into reproducible analysis workflows.
Develop immunogenicity prediction methods by integrating sequence, structure, and experimental data.
Apply structure-based modeling and simulation to characterize biomolecular interactions relevant to immune recognition.
Build and benchmark multimodal ML models combining sequence, structure, and tabular data.
Evaluate model performance and generalizability across modalities.
Contribute to first-author manuscripts and scientific presentations.
Collaborate across computational, biology, and experimental teams and deliver reproducible code and models.

Skills

AlphaFold2/Boltz2

Molecular dynamics

Python

PyTorch

HPC/GPU

Immunology knowledge

Scientific communication

Education

PhD in computational immunology/biology/chemistry/structural biology/bioinformatics

PhD due by Spring 2027

Tools

Python

PyTorch

Job description

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

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

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.

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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San Francisco Residents Only:

We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

Los Angeles Residents Only:

We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance

Employee Status:

Regular

Relocation:

Domestic

VISA Sponsorship:

Yes

Travel Requirements:

10%

Flexible Work Arrangements:

Not Applicable

Shift:

Not Indicated