Relocation Offered: AI Scientist for Target Discovery

Novartis; Basel; Vor Ort; CHF 78.000 - 146.000; Vollzeit

Benefits dieser Stelle

Insurance plans

Retirement plans

Wellbeing resources

Global recognition programs

Flexible and hybrid working options

14 weeks paid parental leave

Zusammenfassung

Novartis is seeking an enthusiastic AI/ML scientist to join the Oncology Data Science team in Biomedical Research. The role focuses on applying advanced AI approaches to generate insights from multi-modal datasets to advance target and biomarker discovery in oncology.

The candidate will work with foundational models, pre-trained and multi-modal systems, and collaborate across teams to ensure ML-ready data and rigorous validation, with opportunities to publish results.

Qualifikationen

• Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field.
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Aufgaben

• Design, develop, implement and apply advanced machine learning algorithms, AI models, and platforms to enable the delivery of predictive insights from pre-clinical, clinical and real-world evidence datasets.
• Demonstrate value of innovative AI techniques in drug target identification, biomolecular interaction modeling, drug development and biomarker discovery.
• Work with foundational models, including pre-trained, self-supervised, multi-purpose, and multi-modal models to advance generative AI applications in drug discovery.
• Collaborate with cross-functional teams to develop and adopt best practices for ML-ready data.
• Contribute to scientific publications and present results at internal and external scientific conferences.

Kenntnisse

Generative AI

Biomedical foundation models

Deep learning

Multi-modal learning

PyTorch

Communication

Ausbildung

Ph.D. in ML/CS/Computational Biology

Tools

ML stack

Data platforms

Jobbeschreibung

Novartis is seeking an enthusiastic AI/ML scientist to join the Oncology Data Science team in Biomedical Research. The role focuses on applying advanced AI approaches to generate insights from multi-modal datasets to advance target and biomarker discovery in oncology.

The candidate will work with foundational models, pre-trained and multi-modal systems, and collaborate across teams to ensure ML-ready data and rigorous validation, with opportunities to publish results.