Applied Researcher in Data-driven Nutrition

CHALMERS TEKNISKA HÖGSKOLA AKTIEBOLAG; Göteborgs kommun; On-site; SEK 450,000 - 600,000; Full time

Benefits offered by this job

Access to international academic and industrial networks

Opportunities for personal and scientific development

Job summary

CHALMERS TEKNISKA HÖGSKOLA AKTIEBOLAG seeks an ambitious applied researcher focusing on data-driven nutrition and health in Gothenburg. This role entails leading research projects and collaborating with domain experts in nutrition, medicine, and AI. The ideal candidate holds a PhD in a related field and has a solid programming background in R or Python.

Join a dynamic research environment at the Fraunhofer-Chalmers Centre and contribute to innovative projects that bridge mathematical and biomedical research.

Qualifications

• Holds a PhD in Applied Mathematics, Mathematical Statistics, or related field.
• Experience in data-driven research related to biomedicine, nutrition, or public health.
• Proficient in statistical modelling and machine learning methods.

Responsibilities

• Lead research projects in data-driven nutrition and health.
• Conduct statistical modelling and analysis of diverse datasets.
• Supervise PhD students and postdocs involved in joint projects.

Skills

Statistical modelling and AI

Programming in R and/or Python

Data-driven research

Interdisciplinary collaboration

Education

PhD in Applied Mathematics or related field

Tools

R

Python

Job description

Overview

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.

Your role

• 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

• 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 modelling, 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.

Meritorious qualifications

• 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

• 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.

Employment details

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)