Research Fellow, Machine Learning

Key Skills

Deep Learning, Effective communication skills, Machine learning techniques, Python Programming, PyTorch, TensorFlow, Transformer

Job Description

The computational chemistry group at Biogen is seeking a creative and self-motivated research fellow to design, develop, and apply new machine learning algorithms for small molecule drug discovery. 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 development and train in an industry research setting. In this role, you will collaborate across medicinal chemistry to leverage machine learning algorithms for small molecule drug discovery.

What You’ll Do

• You will join the growing AI/ML group within computational chemistry as a research fellow, and participate in cutting-edge research in ML and applications to small molecule drug discovery and design.
• You will collaborate closely with cross-functional teams across medicinal chemistry to solve complex problems, including molecular generation, property optimization, and synthesis accessibility.
• You will drive publications in scientific journals and machine learning conferences, and present results at internal and external meetings.

Who You Are

You are a recent Ph.D. graduate with strong self-motivation and eager to make impactful contributions to drug discovery. You will be expected to stay current with the machine learning literature and apply the latest advances to address drug discovery project challenges.

Qualifications

Required Skills

• Ph.D. in computer science or computational science field
• Strong research interest in drug discovery.
• Experience with developing statistical and machine learning models.
• Proficiency in Python and standard ML tools and packages.
• Track record of publications, and/or scientific presentations.
• Should be able to work in a multidisciplinary team.
• Excellent oral and written communication skills.

Preferred Skills

• Hands-on experience in implementing deep learning models (e.g. VAE, GNNs, Transformers, RL)
• Hands-on experience with deep learning framework (Pytorch, TensorFlow).
• Experience in solving real-world problems using deep learning in a multidisciplinary setting is a strong plus.