Vacant job

Postdoctor Researcher in Exposome Analysis

Do you want to work with exposome analysis and metabolomics in a clinically relevant environment, supported by competent and friendly colleagues in an international setting? Do you want an employer that invests in sustainable employment and offers secure, advantageous working conditions? We invite you to apply for a postdoctoral position at Uppsala University.

The Department of Medical Sciences is a large clinical department with approximately 250 employees and over 900 individuals affiliated through Akademiska Sjukhuset (Uppsala University Hospital). The department has a broad research profile with strong research groups in a number of areas. Research takes place in close connection with the clinical operations at Akademiska Sjukhuset and covers both basic studies on disease causes and the development and evaluation of improved diagnostics and new treatment methods. More about the department's activities can be found at www.medsci.uu.se (http://www.medsci.uu.se).

We are now looking for a highly ambitious and proactive postdoctoral researcher to join us, focusing on exposome analysis within clinical questions. Our interdisciplinary activity at Clinical Chemistry, within the Department of Medical Sciences, is located at Akademiska Sjukhuset. Furthermore, we have very high competence in AI and deep learning methods and how these can be used to enable personalized treatment forms in future healthcare.

Responsibilities

You will work in research projects that use advanced statistical models and machine learning to analyze complex biomedical data, including mass spectrometry data and register data (e.g., electronic health records). The tasks include preprocessing, quality control, and analysis of various types of high-dimensional data. You will collaborate in advanced statistical analyses to study relationships between biomarkers, environmental factors, and disease outcomes/courses, as well as visualize and interpret results. Depending on your background, the work may also include analysis of register and journal data, as well as the development and application of machine learning methods. The role also involves documenting workflows and analysis results in accordance with good research practice. Additionally, you are expected to assist with statistical analyses in other projects within the group. You are expected to actively participate in research meetings and collaborate both within your own research group and with external partners.

Qualifications

• PhD in bioinformatics, environmental medicine, or a foreign degree assessed as relevant. The degree must be completed no later than at the time the employment decision is made. Preference is given to those who have obtained their degree within the last three years. When calculating the three-year timeframe, the starting point is the last day of application. If there are special reasons, such a degree may have been obtained earlier.
• At least 5 years of documented experience in preprocessing and quality control of mass spectrometry data
• Documented experience working with untargeted mass spectrometry data
• Documented experience in mass spectrometry-based data analysis and metabolite identification, including the use of tools such as OpenMS and SIRIUS
• Experience in statistical analysis of mass spectrometry data with a focus on metabolomics and exposome analysis, including regression models and survival analyses
• At least 5 years of documented programming experience with R or Python
• Experience analyzing relationships between exposures, register data, and disease outcomes in epidemiological studies
• Experience in teaching and supervising students
• Experience writing scientific articles and research grant applications
• At least one published first-author article with a 5-year Impact Factor over 15
• Very good ability to communicate orally and in writing in English, including scientific documentation

Desirable/Additional Qualifications

• Experience working in clinically relevant research projects, especially those involving the handling and analysis of patient data
• Experience working with the software TraceFinder for detection and quantification of specific substances
• Experience creating and documenting reproducible analysis workflows
• Experience managing large datasets
• Experience working with survey data and data from electronic health records
• Very good ability to communicate orally and in writing in Swedish
• Experience with mixture analyses (quantile G-computation and WQS), survival analyses (Cox proportional hazard model), regression models, and mediation analyses
• Experience with advanced data analysis, including GitHub, Docker/Singularity, Nextflow, machine learning and deep learning models such as graph neural networks, LSTM, Transformers, and CNNs, as well as methods for conformal prediction and explainable AI.

About the Position

The position is fixed-term for two years according to the central collective agreement. The position is full-time. Start date: October 1, 2026, or as agreed. Location: Uppsala

Information about the position can be obtained from: Research Leader Kim Kultima ([email protected]) and Doctor Ida Erngren ([email protected])

Please submit your application by July 28, 2026, Ref: UFV-PA 2026/2345.

Uppsala University is a broad research university with a strong international standing. The ultimate goal is to conduct education and research of the highest quality and relevance to make a difference in society. Our most important asset is all 7,500 employees and 53,000 students who, with curiosity and engagement, make Uppsala University one of the country's most exciting workplaces.

Read more about our benefits and what it is like to work at Uppsala University: https://uu.se/om-uu/jobba-hos-oss/ (https://uu.se/om-uu/jobba-hos-oss/)

The position may be subject to a security check. A prerequisite for employment in the case of a security check is that the applicant is approved.

We decline offers of assistance with recruitment and advertising.

Applications are received via Uppsala University's recruitment system.

Trade Union Representatives: Saco-S - [email protected], Seko - [email protected], ST (OFR/S) - [email protected]