Data Science & AI Innovation Postdoctoral Fellow d42

Darum lohnt es sich

The successful candidate will collaborate across multidisciplinary research teams and contribute to scientific publications and innovation in AI‑driven drug development. /p pbLocation: /b Basel, Switzerlandbr/bDuration: /b 3 yearsbr/bProgram start date: /b October 1, 2026br/bApplication deadline: /b July 15, 2026, end of day /p h3About the Role /h3 pAs a Postdoctoral Research Fellow, you will join data42 in Basel and pursue an innovative research project at the forefront of biomedical science and drug discovery.

You will work with one of the richest biomedical data environments globally, combining clinical, biomarker, and omics datasets from hundreds of thousands of patients across thousands of trials and real‑world data assets for validation and generalization. /p h3Key Responsibilities /h3 ul liDevelop and benchmark machine learning models for treatment effect estimation, patient stratification, and counterfactual outcome prediction from clinical trial data. /li liDesign and evaluate generative AI models for patient trajectory simulation, synthetic cohort generation, and virtual clinical trial applications. /li liDevelop methods that generalize treatment effect models across patient populations, disease cohorts, and clinical indications. /li liApply causal inference and explainable AI approaches to identify predictive and mechanistic biomarkers associated with treatment response and adverse events. /li liDefine and refine ML research strategy and experimental designs to achieve scientific research goals. /li liCollaborate with interdisciplinary teams spanning data science, translational medicine, oncology, immunology, and drug development to address high‑priority scientific questions. /li liDisseminate research through publications, conference attendance, and internal seminars and presentations. /li /ul h3Essential Requirements /h3 ul liPhD (or equivalent doctoral degree) in a relevant scientific discipline completed prior to the fellowship start date. /li liDemonstrated record of scientific achievement (publications, presentations, patents, or equivalent). /li liStrong commitment to learning, innovation, and professional development. /li liStrong foundation in ML (deep learning, probabilistic modeling, or similar) and statistics. /li liDemonstrated experience in deep model development, including architecture and training task design. /li liInterest in biology, clinical data, and/or drug discovery. /li liInterdisciplinary communication skills. /li liEligibility to work in Switzerland. /li /ul h3Desirable Requirements /h3 ul liExperience in causal ML, representation learning, and generative models. /li liExperience working in multidisciplinary teams. /li liExperience developing machine learning models for regulatory applications. /li /ul /p #J-18808-Ljbffr ph3Summary /h3 pThe AI Innovation Postdoctoral Fellow will develop cutting‑edge machine learning and generative AI methods for treatment effect modeling, patient stratification, and virtual clinical trials using large‑scale clinical trial datasets.

The role combines methodological research in causal AI and predictive modeling with real‑world biomedical applications, aiming to improve clinical decision‑making, biomarker discovery, and trial design.

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. /p h3Research Opportunity /h3 pThis unique opportunity enables you to help redefine how clinical trials are analyzed, simulated, and designed.

You will build next‑generation models that learn treatment effects, tackle counterfactual reasoning at the patient level, and explore generative “digital patients” and synthetic trials.