We are seeking an ambitious applied researcher who wants to work at the forefront of data-driven nutrition and health. This is a unique opportunity to bridge mathematics, statistics, AI, and biomedical research in a highly interdisciplinary research environment.
About us
Fraunhofer-Chalmers Centre (FCC) is a leading research centre in industrial mathematics, modelling, simulation, optimisation, and data analytics. We operate at the interface between academic research and industrial needs, often in interdisciplinary projects where mathematics, data, and domain expertise meet.
Together with the nutrition research group led by Professor Rikard Landberg at Chalmers University of Technology, we conduct advanced research in data-driven nutrition, health, and food science. With large-scale diet and health data, omics data, biomarkers, digital food and health services, we establish predictive models for evaluation of the role of diet in health and disease and establish personalized dietary strategies for more effective disease prevention. In many cases, the work involves time series data, dynamic processes and phenomena, where both methods and interpretation must account for temporal dynamics. Data typically comes from intervention studies conducted in Gothenburg and or from large cohorts and biobanks from international collaborators.
To secure and further develop this important collaboration, we are now recruiting an applied researcher with a strong quantitative profile and interest in nutrition, health, or medicine.
Your role
As an applied researcher in this area, you will:
- Act as a key person in the collaboration between FCC and the nutrition research group at Chalmers.
- Lead and conduct research projects in data-driven nutrition, such as:
- analysis of time series data and dynamic processes, where signals and responses evolve over time.
- statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data
- analysis of omics data (metabolomics, proteomics, microbiome, etc.)
- development of predictive dynamical models and digital decision-support tools for nutrition and health
- method development in causal inference, integration of heterogeneous data sources, uncertainty quantification
- Work with a wide range of data types, for example dietary records, biomarkers, omics data, registry data, and sensor data such as CGM measurements (continuous glucose monitoring), activity trackers, and other wearable sensors.
- Serve as a bridge between domain researchers (nutrition, medicine, food science) and quantitative experts (mathematics, statistics, AI&ML, systems engineering).
- Supervise, collaborate, and support PhD students and postdocs involved in joint projects.
Your profile
We are looking for someone who:
- Holds a PhD in Applied Mathematics, Mathematical Statistics, Automatic Control, Signal Processing, Systems Engineering, Data Science, or a related field.
- Has experience in data-driven research, preferably related to biomedicine, nutrition, epidemiology, food science, or public health.
- Is proficient in modern statistical modelling, AI & machine learning methods (e.g. system identification, regression models, mixed-effects modeling, Bayesian methods, deep learning, variational autoencoders, generative AI).
- Is an experienced programmer in R and/or Python, and used to working with large datasets and reproducible analysis workflows.
- Enjoys working in interdisciplinary environments and is curious about understanding biological/nutritional research questions in depth.
It is meritorious if you also:
- Have experience working with cohort data, registry data, clinical studies, or omics data.
- Have previously worked in projects involving both academic and industrial/external partners.
- Have experience supervising PhD students, postdocs, or junior researchers.
- Can communicate in both Swedish and English; excellent English is required.
What we offer
With us, you will:
- Have a unique opportunity to combine advanced quantitative and data-driven methods with cutting-edge research in biomedicine, nutrition, and health.
- Work in a strong and long-term collaboration between Fraunhofer-Chalmers Centre and Chalmers division of Food and Nutrition Science, with access to both international academic and industrial networks.
- Influence the direction of a strategically important initiative in data-driven nutrition and health.
- Be part of a creative, collaborative, and international research environment with good opportunities for personal and scientific development.
Employer: Fraunhofer-Chalmers Research Centre for Industrial Mathematics (Fraunhofer-Chalmers Centre, FCC)
Employment: according to agreement
Location: Gothenburg, Sweden
Department: Systems and Data Analysis (in close collaboration with Chalmers)
Application procedure
The application should be written in English and attached as PDF-files, containing as specified below. Maximum size for each file is 40 MB. Please note that the system does not support Zip files.
- CV
- Publication list
- Transcript of grades
- Personal letter with:
- A brief description of your research profile and how it relates to nutrition/health
- A brief motivation as to why you are interested in this position.
Please apply no later than 16th August 2026. Evaluation of applications will be done on a continuous basis.
Please note: The applicant is responsible for ensuring that the application is complete. Incomplete applications and applications sent by email will not be considered. Contact details to references will be requested after the interview.
For questions, please contact:
Mats Jirstrand, Head of Department, Systems and Data Analysis, Fraunhofer-Chalmers Centre
E-mail: mats.jirstrand@fcc.chalmers.se
Phone: +46 730 794303
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