AI Scientist – AI-Driven Target Identification

Reposted Yesterday
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Hiring Remotely in Basel-City, CHE
Remote
78K-146K Annually
Senior level
Biotech • Pharmaceutical
The Role
Apply advanced AI/ML methods to multi-modal preclinical, clinical and real-world datasets to enable target and biomarker discovery. Develop and deploy generative and foundation models, collaborate cross-functionally, and publish scientific results.
Summary Generated by Built In

Salary Range:

CHF78,400.00 - CHF145,600.00

Job Description Summary

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.

Job Description

 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 Annual

The 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


 

Skills Desired

Biostatistics, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Statistical Analysis, Time Series Analysis

Skills Required

  • Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field.
  • Strong experience in generative AI, biomedical foundation models, geometric deep learning, multi-modal learning, or large-scale knowledge graphs.
  • Proficiency with deep learning frameworks such as PyTorch.
  • Excellent programming skills (Python).
  • 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.
  • Demonstrated strong research skills with publications in top-tier ML/AI conferences and/or leading scientific journals.
  • Excellent communication skills to convey complex data insights to cross-functional teams.

Novartis Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Novartis and has not been reviewed or approved by Novartis.

  • Healthcare Strength Pay and benefits are described as a strong overall package, supported by medical, dental, and vision insurance alongside FSAs/HSAs and disability and life coverage. Mental-health support is reinforced through an employee assistance program with psychological support and a network of mental health first aiders.
  • Retirement Support Retirement support is positioned as a standout element, with an automatic company contribution plus dollar-for-dollar matching in the 401(k). Additional retirement funding is described through an age-based defined contribution program and access to an employee share purchase plan discount.
  • Parental & Family Support Family-related benefits are framed as robust, including a global minimum of paid parental leave for new parents following birth or adoption. Added supports include domestic partner coverage, dependent-care resources, and benefits such as adoption assistance and child/elder care options.

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The Company
HQ: Basel
110,000 Employees
Year Founded: 1996

What We Do

Novartis is an innovative medicines company. Every day, working to reimagine medicine to improve and extend people’s lives so that patients, healthcare professionals and societies are empowered in the face of serious disease. Our medicines reach more than 250 million people worldwide.

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