Summary

At Novartis, we are reimagining medicine to improve and extend people's lives. We use innovative science and technology to address some of society's most challenging healthcare issues. We discover and develop breakthrough treatments and find new ways to deliver them to as many people as possible. In 2020, we touched >800 million patients with our products. How can we continue to advance our science to help even more patients in need? We believe the answers are found when curious, courageous, and collaborative people are empowered to ask new questions, make bolder decisions, and take smarter risks.

In Global Discovery Chemistry (GDC) of Biomedical Research in Basel, Switzerland, we are at the core of Novartis' purpose. We are looking for a highly motivated, passionate researcher with a strong scientific background in data science and/or computational chemistry, a curious mind-set, and cultural agility to invent innovative medicines and advance the frontiers of drug discovery. Join us and help reimagine medicine!

• Work collaboratively in a multidisciplinary team to discover and develop novel therapies across various disease areas.
• Apply, develop and integrate state-of-the-art machine-learning, cheminformatics and physics-based algorithms to accelerate and impact in our portfolio projects.
• Apply data science and statistical methods to develop scientific hypotheses and contribute to data driven drug discovery.
• Combine machine learning with physics-based methods to build & automate advanced computational workflows to enhance our medicinal chemistry projects.
• Discuss and communicate scientific results at project and group meetings, decision boards, and external conferences
• Contribute to patent inventorship and scientific publications
• In addition to pipeline project responsibilities, participate in global initiatives shaping the future of drug discovery at Novartis

• Advanced degree in data science, machine learning, computational chemistry, or related field. Candidates with an experimentalist background and strong computational and/or data science experience are also encouraged to apply.
• Experience in scientific software development/programming (2-3 years), e.g. SOTA ML/scientific software libraries, RDKit, ML Ops, and the scientific Python tech stack.
• Experience in computer-aided drug design, e.g. structure/ligand-based drug design, molecular dynamics, virtual screening, pharmacophore modeling, is beneficial.
• Demonstrated track-record of initiating, leading, or being a key contributor to cutting edge research in data science, machine learning, computational chemistry or life sciences
• An attitude of curiosity, innovation, teamwork, and receptiveness to diverse perspectives, coupled with a passion for personal and professional growth
• Critically interpret results, build new experimental hypotheses, take calculated risks and smart decisions
• Ability to work in a fast-paced team-oriented matrix environment
• Excellent oral and written communication and strong influencing skills