Postdoctoral Researcher – Data Science & Embedded Clinical Trials
Join to apply for the Postdoctoral Researcher – Data Science & Embedded Clinical Trials role at Kanton Bern.
The Faculty of Medicine at the University of Bern is an environment for high‑quality, future‑oriented research. Strong connections between basic research, engineering sciences, and university hospitals enable a unique setting for translational and patient‑centered clinical research. The faculty prioritizes cross‑disciplinary research and digitalization, fostering innovation in medical science. It is one of the largest medical faculties in Switzerland and is affiliated with the country’s largest hospital complex.
The Department of Clinical Research (DCR) is a joint initiative of the University of Bern’s Faculty of Medicine and its university hospitals, including Inselspital and the University Psychiatric Services (UPD). It supports and professionalizes clinical and translational research collaborations. Our specialized divisions assist researchers throughout the entire research process, from project conception to result dissemination. We provide tailored educational programs and events on all aspects of clinical research, equipping researchers and students with the skills to conduct efficient and impactful studies. Our mission prioritizes patient‑centered research, ensuring that patient perspectives are integral to our work.
We are establishing a new team to provide clinical researchers access to trial‑quality real‑world data (RWD) grounded in transparent, evidence‑based validation. This includes conducting outcome validation studies for claims‑based and EHR‑based algorithms, such as disease and disease‑severity phenotyping based on the Inselspital’s EPIC data. This new RWD support team will pave the way for using RWD for clinical trials embedded in routine care, generating timely, randomized real‑world evidence. It will work closely with the Pragmatic Evidence Lab (Prof. Lars Hemkens) and the Medical Data Science Unit (Prof. Benjamin Ineichen) at DCR.
Key challenges and opportunities
* Developing innovative, evidence‑based methods to make RWD trial‑ready.
* Integrating RWD into conventional clinical trial databases.
* Evaluating the reliability of RWD for trials, e.g., testing where EPIC‑based RWD can replace manual adverse event assessments.
* Systematically assessing the validity of trial outcomes derived from routine data through empirical research, validation studies, and meta‑research.
* Defining how to make best use of health data for patient‑centered, pragmatic research.
Your Role
* Contribute to the conceptualization, setup, and implementation of a state‑of‑the‑art RWD team at DCR.
* Develop innovative methods and frameworks to assess and measure data‑quality from the perspective of clinical trial applications.
* Conduct meta‑research and validation studies for outcome and/or phenotyping algorithms using routine data.
* Co‑design research protocols, data pipelines, and governance frameworks for RWD‑based phenotyping.
* Adapt and translate established models of EPIC/EHR use from other institutions to the University of Bern.
* Support protocol design for randomized trials, ensuring regulatory compliance and methodological rigor from a data perspective.
* Collaborate with clinical researchers, data scientists, and international partners to embed research into care.
* Contribute to grant writing and fundraising efforts to ensure sustainability of the academic team.
* Train and mentor junior researchers and students in RWD and validation methods.
* Disseminate findings through high‑impact publications and conference presentations.
Your Profile
* MD and/or PhD in clinical research (epidemiology, biostatistics, or a related field will be considered).
* Hands‑on experience in medical data science/biomedical informatics.
* Hands‑on experience with clinical trial design, conduct, and/or analysis, supported by a publication record.
* Experience in working with RWD and/or validation or meta‑research, supported by a publication record.
* Advanced programming and data management skills, including data engineering (e.g., Python, R, SQL; EPIC/Caboodle experience is a plus).
* Ability to efficiently work independently under tight deadlines with general guidance in multidisciplinary teams.
* Ability to prepare manuscripts, grant proposals, and scientific meeting presentations.
* Fluency in English (German is an asset).
We offer
* An academic role at the intersection of data science, clinical research, and advanced trial methodology, with real impact on patient‑centered evidence generation.
* The opportunity to help establish a new RWD support team at DCR Bern, directly enabling research that is embedded in care.
* A supportive academic environment with opportunities for career development, mentoring, publications, and independence.
* A strong commitment to open science and publication in peer‑reviewed scientific articles.
* Access to a dynamic machine learning community at the University of Bern, with a strong emphasis on digitalization (see digitalization strategy).
* Integration in a wide network of clinical researchers and meta‑researchers locally, nationally and internationally.
* Collaboration within Switzerland’s largest medical faculty and hospital complex, offering extensive networking opportunities.
* Competitive employment conditions under University of Bern regulations.
Salary
Salary will be defined based on the highest degree of the applicant. Salary classifications from the University of Bern apply. More information can be found here.
Start of employment
Start date preferentially as soon as possible but with some flexibility (latest spring 2026).
Place of work
Freiburgstrasse 3, sitem‑insel (https://sitem‑insel.ch/en/), Bern, Switzerland.
Contact
Before applying, we strongly recommend you discuss the position and your suitability with Prof. Eva Segelov (Eva.segelov@unibe.ch), Prof. Benjamin Ineichen (Benjamin.ineichen@unibe.ch), and Prof. Lars Hemkens (Lars.hemkens@unibe.ch). Applications open until 15 November 2025.
Application documents
* CV, including publications
* Motivation letter explaining your interest in this particular project and environment
* Academic transcript/record of grades
Note: Only complete applications will be considered. We will invite promising candidates for an interview.
www.karriere.unibe.ch
#J-18808-Ljbffr