Innovation Postdoctoral Fellow, Data Science & AI Vision Foundation Models Cellular Imaging

The Novartis Biomedical Research Postdoctoral Fellowship Program offers a unique training opportunity for exceptional early‑career scientists eager to advance AI‑powered phenotypic drug discovery. The fellowship is a full‑time, up‑to‑three year program beginning October1,2026 and will be hosted by the Discovery Sciences (DSc) group in San Diego. Candidates may also be considered for positions in Basel or Cambridge.

As a Postdoctoral Research Fellow you will develop foundation models for high‑content cellular imaging, working alongside leading scientists in a highly collaborative, multidisciplinary environment. You will gain exposure to the broader ecosystem that translates scientific discovery into medicines and have opportunities to publish in leading machine‑learning and biomedical venues.

This fellowship aims to advance representation learning for high‑content cellular imaging to accelerate AI‑powered phenotypic drug discovery across Novartis. The project will develop, benchmark, and deploy foundation models that generalize across assays, perturbations, cell types, and imaging modalities. You will curate large‑scale microscopy datasets, pretrain and adapt vision foundation models, and design rigorous evaluation protocols to assess model performance, robustness, and generalization on public and proprietary datasets.

The project will deliver a unified platform for training, benchmarking, and deploying foundation models for high‑content cellular imaging, supporting downstream applications that raise the accuracy, scalability, and reproducibility of phenotypic analysis across Novartis.

• Develop vision foundation models for high‑content cellular imaging using state‑of‑the‑art self‑supervised learning techniques.
• Design robust evaluation protocols that measure how well models generalize to unseen assays, perturbations, cell types, and imaging conditions.
• Curate large‑scale public and internal microscopy datasets and establish standards for data quality and reproducibility.
• Extend the models to multimodal settings by integrating imaging with other data modalities, such as compound data, for drug discovery applications.
• Build scalable training and inference pipelines across high‑performance computing and cloud infrastructure with clean, reproducible, and well‑documented code.
• Propose innovative modeling and evaluation methods that advance the team’s technical direction.
• Work independently and collaboratively with data scientists across disease area, platform, and AI research teams, and publish and present results.

• 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 (PhD conferred in 2026 only).
• Demonstrated record of scientific achievement (publications, presentations, patents, or equivalent).
• Strong commitment to learning, innovation, and professional development.
• Ability to formulate and drive independent research questions.
• Proficiency in Python and modern deep‑learning frameworks (e.g., PyTorch, Tensor Flow, or JAX), with hands‑on experience training models on GPUs.
• Experience training deep‑learning models on HPC or cloud infrastructure with reproducible code.
• Working knowledge of vision foundation models, including self‑supervised learning and vision transformers, with experience fine‑tuning or adapting pretrained models to new tasks.
• Experience designing benchmarking and evaluation protocols for model generalization.
• Strong written and verbal communication skills.

• Experience pretraining vision foundation models from scratch on large‑scale imaging datasets.
• Expertise in high‑content or biomedical imaging (e.g., Cell Painting, phenomics, digital pathology) and channel‑adaptive or multimodal architectures.
• Experience with distributed training on HPC clusters, reproducible ML pipelines on cloud infrastructure, and model‑tracking tools such as MLflow.
• Publications at top ML venues (NeurIPS, ICML, ICLR, CVPR) or biomedical ML venues (MICCAI, etc.).

Please submit your CV and cover letter by July
25,2026. In your cover letter, describe your research interests, career aspirations, and how participation in the Novartis Biomedical Research Postdoctoral Fellowship Program will support your long‑term development. Confirm your availability to start on October1,2026.

The starting salary for this position is $87,000 USD per year. US‑based eligible employees receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. Employees are also eligible for a generous time‑off package including vacation, personal days, holidays, and other leaves.