aipythonpytorchgenerative aibioinformaticsantibody designstructural biologyprotein engineeringmulti omicscomputational drug discovery
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
$146к-192к/год
$160к$170кмедиана$200к
По похожим ролям (49) ~ $170к/год
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Крутая вакансия
развернуть
Задачи внятно связаны с разработкой лекарств и современными методами ИИ и структурной биологии; при этом это узкая руководящая специализация с работой на месте в США.
Principal Scientist, Bioinformatics (AI): Developing generative AI models and agentic AI systems for novel disease-target discovery and designing high-affinity binders for CAR-T therapies with an accent on multi-omic analysis, structural biology, and geometric deep learning. Focus on engineering protein binders, modeling paratope-epitope interactions, optimizing biophysical properties, and reducing off-tumor toxicity.
Location: Somerset, New Jersey, United States; onsite. Applicants must be authorized to work in the United States.
Base pay: $146,410–$192,164 USD per year. Performance-based bonus and/or equity may be available for eligible roles.
Company
hirify.global is a biotechnology company developing cell-based therapies, including CAR-T, TCR-T, NK cell-based, and other emerging platforms.
What you will do
Architect and deploy agentic AI systems to mine multi-omic datasets, clinical literature, and biological pathways for novel tumor-specific drug targets.
Build predictive frameworks using transcriptomics and other datasets to evaluate target druggability and potential off-tumor toxicity.
Develop and adapt generative models, including protein language models, diffusion models, and inverse-folding algorithms, to design specific binders for tumor antigens.
Use geometric deep learning and structural biology to model paratope-epitope interactions and support CAR-T binder design.
Inspect and refine AI-designed binders by addressing physical anomalies, steric clashes, backbone strain, hydrophobic packing, and hydrogen-bonding networks.
Optimize binder biophysical properties to support CAR-T signaling and prevent T-cell exhaustion.
Requirements
Ph.D. in Computational Biology, Computer Science, Structural Biology, or Biophysics.
3+ years of post-Ph.D. experience, or 6+ years for MS/BS, in the biotechnology or pharmaceutical industry or an advanced research setting focused on computational drug discovery, target identification, and antibody or binder design.
Expert programming proficiency in Python and deep learning frameworks, primarily PyTorch.
Experience building generative AI models and agentic AI systems using LLM orchestration frameworks to query biomedical databases and literature.
Deep familiarity with AlphaFold, ESMFold, RFdiffusion, ProteinMPNN, BindCraft, and FoldFlow.
Proficiency with physics-based simulation and structural optimization or visualization tools, including GROMACS, AMBER, OpenMM, and PyMOL.
Solid understanding of structural immunology and expertise in interface biophysics, including calculating interface binding energies (ΔΔG) and evaluating electrostatic surface potentials.
Familiarity with multi-omics platform datasets and target evaluation databases, including TCGA, Open Targets, Human Protein Atlas, and DepMap.
Culture & Benefits
Permanent full-time employees receive medical, dental, and vision insurance.
Benefits include a 401(k) retirement plan with a company match that fully vests on day one.
Eight weeks of paid parental leave are available after three months of employment.
Paid time off includes vacation, personal time, sick time, floating holidays, and eleven company holidays.
Additional benefits include flexible spending and health savings accounts, disability coverage, life and AD&D insurance, commuter benefits, family planning and care resources, and well-being initiatives.
Contractors are not eligible for benefits through hirify.global.
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