Machine Learning Intern
15 hours ago
Bristol Myers Squibb is seeking a highly motivated and talented Machine Learning Intern to join our team and contribute to a cutting-edge project aimed at harnessing advances in structure prediction by deep learning models.
As part of the Protein Homeostasis team of the Informatics and Predictive Sciences (IPS) department, this internship position is responsible for adapting and developing novel structure-based generative models to enable targeting of the ubiquitin proteasome system (UPS) and other protein homeostasis pathways.
Key Responsibilities:- Preprocess and analyze structural and biochemical datasets.
- Adapt, develop, and implement generative machine learning models.
- Evaluate and optimize model performance.
- Collaborate with team members and communicate findings, methodologies, and results.
- Present findings at the final internship presentation.
Currently pursuing a PhD in Computer Science, Data Science, Machine Learning, or a related field.
Experience with deep learning frameworks (pyTorch, TensorFlow, etc).
Experience working with biochemical datasets (e.g. protein sequences or structures).
Knowledge of statistics and mathematics.
Preferred experiences:
- Experience with generative ML models.
- Experience working with 3D structures.
- Knowledge of biology, chemistry, and physics.
Bristol Myers Squibb is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, pregnancy, citizenship, marital status, gender expression, genetic information, political affiliation, or any other characteristic protected by law.
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