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Research Fellow, Machine learning, Protein Design
2 months ago
About This Role
At Biogen Computational Science Group, we are revolutionizing drug discovery with cutting-edge machine learning methods. We are seeking a creative and self-motivated research fellow to design, develop, and apply new machine learning algorithms for biologic 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 with various functions within the BTMS organization to develop and deploy cutting-edge machine learning approaches to challenging therapeutic biologic discovery and optimization objectives.
What You’ll Do
You will join the growing AI/ML group within computational science group as a research fellow and participate in cutting-edge research in machine learning and applications to antibody drug discovery and design.
- You will collaborate closely with cross-functional teams across BTMS to solve complex problems including de novo design, multi-parameter optimization, inverse folding, sequence-structure-function modeling and more.
- 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 PhD 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.
Required Skills
- Ph.D. in Computer Science or computational science field.
- Strong research interest in drug discovery.
- Hands-on experience implementing deep learning models (e.g., Transformers, GNNs, RL).
- Extensive experience with deep learning and distributed training frameworks such as PyTorch/TensorFlow and DeepSpeed.
- Mastery of Python and PyTorch.
- Proven track record of publications and/or scientific presentations in machine learning.
- Excellent oral and written communication skills.
Preferred Skills
- Experience with in developing machine learning models, especially LLMs, from various aspects including pretraining, finetuning is a strong plus.
- Familiarity with modern deep learning architectures such as Diffusion models, Transformers, Graph Neural Networks, Flow-based models, etc.
- Experience in solving real-world scientific problems using deep learning in a multidisciplinary setting is a plus.
- Experience with state-of-the-art protein design deep learning model, such as AlphaFold2, RoseTTAFold, RFdiffusion, etc.
Additional Information
Why Biogen?
We are a global team with a commitment to excellence, and a pioneering spirit. As a mid-sized biotechnology company, we provide the stability and resources of a well-established business while fostering an environment where individual contributions make a significant impact. Our team encompasses some of the most talented and passionate achievers who have unparalleled opportunities for learning, growth, and expanding their skills. Above all, we work together to deliver life-changing medicines, with every role playing a vital part in our mission. Caring Deeply. Achieving Excellence. Changing Lives.
At Biogen, we are committed to building on our culture of inclusion and belonging that reflects the communities where we operate and the patients we serve. We know that diverse backgrounds, cultures, and perspectives make us a stronger and more innovative company, and we are focused on building teams where every employee feels empowered and inspired. Read on to learn more about our DE&I efforts.
All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, sexual orientation, marital status, race, color, national origin, ancestry, ethnicity, religion, age, veteran status, disability, genetic information or any other basis protected by federal, state or local law. Biogen is an E-Verify Employer in the United States.
