Research Fellow, ML Application for Molecular Modeling & Design across Discovery Modalities

Key Skills

Bioinformatics, Drug Discovery, Effective communication skills, Machine learning techniques, Molecular biology

Job Description

Our Biotherapeutics and Medicinal Sciences department is seeking a highly motivated PhD scientist to develop Machine Learning (ML) and/or bioinformatics methods to aid drug discovery across four therapeutic modalities - biologics, gene therapy/viral delivery, small molecules or antisense oligonucleotides. Working in our Biologics Structure and Modeling group, you will collaborate closely with our Antibody Discovery group on integrating ML and computational protein modeling/design with wet-lab experiments at various throughput levels. The Research Fellow role at Biogen is an 18-month position designed to provide a unique opportunity for scientists to gain exposure to drug discovery and train in an industry research setting.

What you will do:

• Develop, train and test ML and/or bioinformatics methods that learn determinants of antibody fitness for developability, stability, and/or affinity, and use these to select candidates to carry forward
• Devise, train, refine, and deploy deep neural network models using public and proprietary sequence, structure, property or function data
• Collaborate closely with experimental scientists to create a model-test-learn loop
• Collaborate with internal stakeholders and with external (academia or industry) partners
• Develop and apply modeling and design strategies for proteins, antibodies, AAV capsids, or other modalities
• Keep abreast of state-of-the-art technologies in the field
• Present scientific findings to broad audiences including senior leadership to drive decision making in program teams

Requirements:

• PhD in a field related to computational protein design such as Chemical and Biomolecular Engineering, Bioengineering, Molecular Biology, Biochemistry, Chemistry, Biophysics, Computer Science, Mathematics, Statistics, Physics, or Computational Biology
• Experience with devising and implementing ML methods for protein or antibody modeling or design, or with deep learning methods that relate protein sequence, structure, property or function (e.g., structure prediction, annotation, novel or variant sequence generation, property prediction, directed evolution, etc.)
• Strong communication, collaboration and interpersonal skills
• Strong publication record in peer-reviewed journals
• Strong problem-solving and troubleshooting skills
• Independent and curious self-starter
• Legal authorization to work in the U.S.

About us

Biologics Structure and Modeling is a highly cross-functional team that primarily supports Biologics Drug Discovery by solving protein apo and complex structures (cryo-EM, X-ray crystallography, NMR), by computationally or rationally modeling, engineering, or designing biologics, and by advising our stakeholders on structural aspects of protein-protein interactions and how mutations affect biology. Beyond Biologics Drug Discovery, and as part of a four-modality company, we partner with colleagues in gene therapy, computational chemistry, and computational biology, supporting Biogen portfolio programs across all therapeutic areas including Alzheimer’s disease and dementia, Parkinson’s disease, Amyotrophic lateral sclerosis (ALS) and multiple sclerosis.