Deep Learning Scientist II, Protein Sciences
Repertoire Immune Medicines
Summary
Repertoire Immune Medicines is seeking a Deep Learning Scientist II to join the Artificial Immune Intelligence Team to accelerate the discovery and development of transformative therapeutics, exploiting proprietary datasets about T cell receptors interacting with peptide-MHC complexes.
Job description
Role Overview
Repertoire Immune Medicines is seeking a Deep Learning Scientist II to join the Artificial Immune Intelligence Team to accelerate the discovery and development of transformative therapeutics, exploiting proprietary datasets about T cell receptors interacting with peptide-MHC complexes.
Key Responsibilities
- Develop novel deep learning approaches spanning protein language models, structural modeling, and multi-modal representation learning to reason about the TCR-pMHC synapse.
- Apply problem-appropriate machine learning, statistics, computational biology, and data science techniques, working closely with wet-lab scientists to understand assay technologies.
Qualifications/Experience
- PhD in computer science, computational biology or a related quantitative field, with 2-5 years of industry experience in protein engineering and design.
- Hands-on experience with training and fine-tuning protein language models (PLMs) and structure-prediction models, and in the development of applied AI pipelines for biological data.
- Ability to reason about protein-protein interactions through rational structure-based approaches, using physics-based methods and machine learning workflows.
- Strong programming skills in Python, including multi-GPU training with PyTorch and related libraries.
- Proven ability to analyze and model complex, high-dimensional biological datasets using sound computational and statistical practices to drive novel insights.
- Experience working with TCR-pMHC binding is a strong plus.
- Intellectual curiosity, scientific rigor, and enthusiasm for working in a fast-paced, evolving research environment.
Requirements
- PhD in computer science, computational biology or a related quantitative field
- 2-5 years of industry experience in protein engineering and design
- Hands-on experience with training and fine-tuning protein language models (PLMs) and structure-prediction models
- Experience developing applied AI pipelines for biological data
- Ability to reason about protein-protein interactions through rational structure-based approaches
- Experience with physics-based methods and machine learning workflows
- Strong programming skills in Python
- Experience with multi-GPU training with PyTorch and related libraries
- Proven ability to analyze and model complex, high-dimensional biological datasets
- Sound computational and statistical practices
- Experience working with TCR-pMHC binding is a strong plus
- Intellectual curiosity, scientific rigor, and enthusiasm for working in a fast-paced, evolving research environment
Benefits
- Medical, Dental & Vision
- Life Insurance
- Flexible Time Off
- 401(k) Retirement Plan
- Short-term Incentive Opportunities
- Long-term Incentive Opportunities
Company overview
Repertoire Immune Medicines is a biotechnology company pioneering the development of novel immune-based therapeutics through its proprietary DECODE platform. The company focuses on discovering and developing T-cell receptor (TCR)-based medicines for cancer and autoimmune diseases. By leveraging advanced computational biology and high-throughput sequencing technologies, Repertoire aims to map the complete repertoire of T-cell receptors and identify disease-specific targets. The company's innovative approach combines immunology expertise with machine learning to decode the immune system's language and develop precision immunotherapies. Based in Cambridge, Massachusetts, Repertoire Immune Medicines represents a cutting-edge convergence of immunology, genomics, and computational science to create transformative treatments for patients with serious diseases.