AI Scientist – AI-Driven Target Identification
About this opportunity
Location: Basel or Cambridge Onsite Relocation is offered for this role. #LI-Onsite The Oncology Data Science team in Biomedical Research at Novartis works at the intersection of oncology drug discovery, computational biology, AI/ML, and data engineering. We are seeking an enthusiastic AI/ML scientist with strong curiosity for AI-driven drug discovery to join the AI & Innovation team. This role will apply advanced AI approaches to generate insights from complex multi-modal datasets and advance our target and biomarker discovery efforts.
Key responsibilities: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 the context of 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.Requirements:Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field.Strong experience in one or more of the following areas: generative AI, biomedical foundation models, geometric deep learning, multi-modal learning, and large-scale knowledge graphs.Excellent programming skills and proficiency in deep learning frameworks such as PyTorch, with openness to learning new tools and technologies.Practical experience across ML and LLM software stack, including feature engineering, model development, deployment, and validation.Prior experience working with omics data and familiarity with oncology drug development.Excellent communication skills, with the ability to communicate complex data insights and recommendations to cross-functional teams.Demonstrated strong research skills, evidenced by publications in top-tier ML/AI conferences and/or leading scientific journals.Rewards At Novartis, we’re committed to reimagining medicine together - and rewarding the people who make it happen. The rewards of being part of our team go far beyond base pay and incentives. We also offer a variety of competitive benefits in kind to help you thrive personally and professionally, such as insurance plans, retirement plans, wellbeing resources and global recognition programs. In addition, we provide flexible and hybrid working options, where possible, and a minimum of 14 weeks paid parental leave. Expected Annual Base Salary Range for role: Switzerland: 78,400.00 - 145,600.00 CHF AnnualThe salary offered is determined based on gender-neutral objectives, such as relevant skills, competencies and experience in accordance with the Novartis pay setting policy and upon joining Novartis will be reviewed periodically. In addition to your base salary, you may be eligible for a performance-based bonus depending on certain performance parameters. Further details will be provided during the application process. Pay equity is a fundamental principle of our employment policy and reflects our commitment to create a diverse, equitable and inclusive environment that treats all employees with dignity and respect, as outlined in our Code of Ethics. Read our brochure to learn more about our global total rewards offering: https://www.novartis.com/sites/novartis_com/files/novartis-life-handbook.pdf Note: Benefits and compensation may vary by country and are subject to local legal requirements, including provisions of collective bargaining agreements where applicable. A full overview of your compensation package, including any relevant collective bargaining agreement details applicable to your role based on your employment location and Novartis employer entity, will be communicated separately to you during the application process. Commitment to Diversity and Inclusion / EEO paragraph: Novartis is committed to building an outstanding, inclusive work environment and diverse teams’ representative of the patients and communities we serve. Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture Benefits and Rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards
Job details
How this role compares
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We currently track 292 comparable Data & Digital roles across 41 biopharma companies.
Salary context
60 of 292 peers report a salary range (USD, annualized)
Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.
Where these roles are based
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Seniority mix
158 of 292 peers have a known seniority level
Therapeutic area mix
6 of 292 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
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Matched on job function only -- seniority, specialty, and location weren't confirmed as aligned.
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.