Summary The Novartis Biomedical Research Postdoctoral Fellowship Program offers a 3-year 100% position starting October 1, 2026, in Basel, Switzerland, focusing on foundational multimodal proteochemometrics models in drug discovery. This opportunity enables early-career scientists to work with cutting-edge AI and biomedical research technologies in a collaboration with data and wet-lab scientists. The fellows will train and optimize structure affinity models using high-throughput experimental data and evaluate their predictive performance for drug-target interactions in hit finding and safety assessments.
About the Role About the Role
We are excited to invite applications for the Novartis Biomedical Research Postdoctoral Fellowship Program, a unique training opportunity designed for exceptional early-career scientists eager to tackle some of the most challenging problems in biomedical research and drug discovery.
As a Postdoctoral Research Fellow, you will join Discovery Sciences in Basel and pursue an innovative research project at the forefront of biomedical science and drug discovery. You will work alongside leading scientists in a highly collaborative, multidisciplinary environment while gaining exposure to the broader ecosystem that translates scientific discovery into medicines.
Our fellows are empowered to ask bold scientific questions, apply cutting-edge technologies, and develop approaches that have the potential to transform patient care.
Research Opportunity
Foundational structure activity models that can predict small molecule protein interactions from the small molecule structure and protein sequence have attracted scientific attention. However, the practical suitability of such models trained on public structure activity data has been limited as this data is both low in volume and extremely sparse. Industrial large scale screening technologies such as DNA encoded libraries generate larger volumes of dense data. In this project we aim at training a large- proteochemometrics model based on high-throughput experimental data resulting from different read-out modalities and will assess how such models can be predictive for low-volume high quality affinity data with and without fine-tuning on a small number of such quality data points.
Why Join the Program?
The Novartis Biomedical Research Postdoctoral Fellowship Program is designed to develop the next generation of scientific leaders, powering the future of medicine, through rigorous research, and immersive learning experiences, such as implementation of AI tools in biomedical research.
Postdoctoral Research Fellows benefit from:
Guidance from accomplished scientific leaders and subject matter experts
Access to advanced technologies, platforms, and research capabilities
Collaboration across disciplines and organizational boundaries
A global and diverse community of postdoctoral fellows
Dedicated programming designed to help fellows thrive throughout their careers.
Personalized experiential learning opportunities through a Postdoc Practicum that empower fellows to explore new scientific domains, build cross-functional expertise, and expand their impact beyond their primary research project.
Opportunities to present research, publish in leading journals, and build an international scientific network
We are entering a new era of biomedical research breakthroughs through the convergence of biology, technology, and artificial intelligence tools, and fellows are also supported in engaging with these emerging approaches.
This is a 100% training position of up to three years in duration.
Reimagining Medicine Together
At Novartis, our purpose is to reimagine medicine to improve and extend people’s lives. Through this program, you will grow as a scientist and future leader while contributing to discoveries that may ultimately benefit patients worldwide.
Key Responsibilities
Train and optimize foundational structure affinity models on high volume experimental data such as DNA encoded library screening data.
Fine-tune models on high-quality low volume affinity data.
Evaluate the performance of the models with and without fine-tuning and compare it with the state-of-the-art models.
Apply and evaluate promising model architectures prospectively in small molecule hit-finding projects.
Evaluate the performance of the models to predict off-targets for pharmacology safety assessments.
Essential Requirements
PhD (or equivalent doctoral degree) in a relevant scientific discipline completed prior to the fellowship start date. The program is intended for scientists immediately following their PhD training (graduated in 2026)
Demonstrated record of scientific achievement (publications, presentations, patents, or equivalent)
Strong commitment to learning, innovation, and professional development Hands-on experiencewith cheminformatic workflows, and familiarity with descriptors and machine learning and deep learning in the context of cheminformatics.
Expertiseworking inLinuxhigh performancecomputing and cloud environments.
Expertisein Python scientific and deep learning stacks,familiarity with best practices in computational reproducible research (version control, testing, documentation).
Experience in training foundational models and / or processing huge datasets
Demonstrated abilityto work as part of an interdisciplinary team (i.e., biologists, chemists, data scientists), withproactive and results-orientedcommunication skills.Dedication to promotingmutualrespect,empathy,andpositivityin diverseprofessionalsettings.
Desirable Requirements
Experience with some of the following: ligand protein docking, ligand proteinco-folding, drug-target interaction models
Experience using synthons and transformations to generate virtual spaces, or to interrogate virtual spaces
#J-18808-Ljbffr
About the Role About the Role
We are excited to invite applications for the Novartis Biomedical Research Postdoctoral Fellowship Program, a unique training opportunity designed for exceptional early-career scientists eager to tackle some of the most challenging problems in biomedical research and drug discovery.
As a Postdoctoral Research Fellow, you will join Discovery Sciences in Basel and pursue an innovative research project at the forefront of biomedical science and drug discovery. You will work alongside leading scientists in a highly collaborative, multidisciplinary environment while gaining exposure to the broader ecosystem that translates scientific discovery into medicines.
Our fellows are empowered to ask bold scientific questions, apply cutting-edge technologies, and develop approaches that have the potential to transform patient care.
Research Opportunity
Foundational structure activity models that can predict small molecule protein interactions from the small molecule structure and protein sequence have attracted scientific attention. However, the practical suitability of such models trained on public structure activity data has been limited as this data is both low in volume and extremely sparse. Industrial large scale screening technologies such as DNA encoded libraries generate larger volumes of dense data. In this project we aim at training a large- proteochemometrics model based on high-throughput experimental data resulting from different read-out modalities and will assess how such models can be predictive for low-volume high quality affinity data with and without fine-tuning on a small number of such quality data points.
Why Join the Program?
The Novartis Biomedical Research Postdoctoral Fellowship Program is designed to develop the next generation of scientific leaders, powering the future of medicine, through rigorous research, and immersive learning experiences, such as implementation of AI tools in biomedical research.
Postdoctoral Research Fellows benefit from:
Guidance from accomplished scientific leaders and subject matter experts
Access to advanced technologies, platforms, and research capabilities
Collaboration across disciplines and organizational boundaries
A global and diverse community of postdoctoral fellows
Dedicated programming designed to help fellows thrive throughout their careers.
Personalized experiential learning opportunities through a Postdoc Practicum that empower fellows to explore new scientific domains, build cross-functional expertise, and expand their impact beyond their primary research project.
Opportunities to present research, publish in leading journals, and build an international scientific network
We are entering a new era of biomedical research breakthroughs through the convergence of biology, technology, and artificial intelligence tools, and fellows are also supported in engaging with these emerging approaches.
This is a 100% training position of up to three years in duration.
Reimagining Medicine Together
At Novartis, our purpose is to reimagine medicine to improve and extend people’s lives. Through this program, you will grow as a scientist and future leader while contributing to discoveries that may ultimately benefit patients worldwide.
Key Responsibilities
Train and optimize foundational structure affinity models on high volume experimental data such as DNA encoded library screening data.
Fine-tune models on high-quality low volume affinity data.
Evaluate the performance of the models with and without fine-tuning and compare it with the state-of-the-art models.
Apply and evaluate promising model architectures prospectively in small molecule hit-finding projects.
Evaluate the performance of the models to predict off-targets for pharmacology safety assessments.
Essential Requirements
PhD (or equivalent doctoral degree) in a relevant scientific discipline completed prior to the fellowship start date. The program is intended for scientists immediately following their PhD training (graduated in 2026)
Demonstrated record of scientific achievement (publications, presentations, patents, or equivalent)
Strong commitment to learning, innovation, and professional development Hands-on experiencewith cheminformatic workflows, and familiarity with descriptors and machine learning and deep learning in the context of cheminformatics.
Expertiseworking inLinuxhigh performancecomputing and cloud environments.
Expertisein Python scientific and deep learning stacks,familiarity with best practices in computational reproducible research (version control, testing, documentation).
Experience in training foundational models and / or processing huge datasets
Demonstrated abilityto work as part of an interdisciplinary team (i.e., biologists, chemists, data scientists), withproactive and results-orientedcommunication skills.Dedication to promotingmutualrespect,empathy,andpositivityin diverseprofessionalsettings.
Desirable Requirements
Experience with some of the following: ligand protein docking, ligand proteinco-folding, drug-target interaction models
Experience using synthons and transformations to generate virtual spaces, or to interrogate virtual spaces
#J-18808-Ljbffr
Data Science & AI Innovation Postdoctoral Fellow Foundational & Multimodal Proteochemometrics models Arbeitgeber: Stiftung Weizenkorn
Unser Kunde ist ein hervorragender Arbeitgeber, der in Basel eine internationale Finanzdienstleistungsorganisation mit einer starken Risikokultur und einem stabilen Governance-Rahmen bietet. Die Mitarbeiter profitieren von überdurchschnittlicher Versicherungsdeckung, einem Beitrag zur Krankenversicherung sowie Essenszulagen, während sie in einem dynamischen, analytikorientierten Umfeld arbeiten, das unabhängiges Denken und persönliche Weiterentwicklung fördert. Die Möglichkeit, eng mit Portfolio-Managern und Führungskräften zusammenzuarbeiten, ermöglicht es den Mitarbeitern, ihre Fähigkeiten in der Risikoanalyse und Performance-Überwachung weiter auszubauen und einen bedeutenden Einfluss auf Investitionsentscheidungen zu haben.
