Senior ML Scientist: Causal AI for Drug Discovery

Roche; Basel; In loco; CHF 60.000 - 90.000; Tempo pieno

Descrizione del lavoro

Roche in Basel is seeking a PhD-level researcher to design and benchmark novel machine learning algorithms for biological challenges. You will work across Basel, New York, and San Francisco, leveraging causal representation learning to push drug discovery forward.

The role emphasizes open science, collaboration, and high-impact publications. You should have strong ML theory, hands-on deep learning with PyTorch, and a track record of scientific contributions.

Competenze

• Solid grounding in machine learning theory and principles.
• Strong practical research experience.
• Experience with causal representation learning or out-of-distribution generalization is a plus.
• Experience publishing in premier ML venues (NeurIPS/ICML/ICLR).

Mansioni

• Design and benchmark novel ML algorithms grounded in causal representation learning.
• Frame foundational research questions for drug discovery.
• Collaborate with cross-functional teams across Basel, NY, and SF.
• Build and scale unconventional neural architectures using deep learning frameworks.
• Translate biological challenges into rigorous computational models.
• Publish high-impact scientific papers for top venues.
• Present findings at internal and international conferences.
• Engage in knowledge-sharing and code reviews to advance capabilities.

Conoscenze

Deep neural networks

PyTorch

Research collaboration

Communication

Formazione

PhD in Computer Science, Statistics, Applied Mathematics, Computational Biology, Physics, or related field

Strumenti

PyTorch

Descrizione del lavoro

Roche in Basel is seeking a PhD-level researcher to design and benchmark novel machine learning algorithms for biological challenges. You will work across Basel, New York, and San Francisco, leveraging causal representation learning to push drug discovery forward.

The role emphasizes open science, collaboration, and high-impact publications. You should have strong ML theory, hands-on deep learning with PyTorch, and a track record of scientific contributions.