Postdoc in mass spectrometry and deep learning Full-time

Postdoc in Mass Spectrometry and Deep Learning

The Department of Clinical Medicine at Faculty of Health at Aarhus University invites applications for a position as Postdoc in the field of clinical bioinformatics as per 15 September 2026 or as soon as possible thereafter. The position is a fixed-term full-time position for 3 years.

As a Postdoc at the Department of Clinical Medicine, you will be part of what is probably the largest health science research department in Denmark. Our clinical research covers all the medical specialities and takes place in close collaboration with the university hospital and the regional hospitals in the Central Denmark Region. We have approx. 30,000 square metres of modern research facilities for experimental surgery and medicine, animal facilities and also advanced scanners at our disposal. The department has overall responsibility for the Master's degree programs in medicine and in molecular medicine. At the department we are approx. 670 academic employees, 500 PhD students and 160 technical/administrative employees who are cooperating across disciplines.

Your daily workplace will be at the Section for Bioinformatics and Computational Biology (BiRC, www.birc.au.dk) located in the University City (Aarhus University Campus). We are a group of researchers and students with a background in a number of different disciplines, including biology, molecular biology, statistics, chemistry, and computer science.

We are seeking a postdoctoral researcher to join an interdisciplinary team developing deep learning models for antimicrobial resistance (AMR) detection directly from MALDI-TOF mass spectrometry data. The project is funded through the ODIN Grant program and is embedded in a broader initiative (AIMS) spanning clinical diagnostics, bioinformatics, and mass spectrometry methodology. It combines immediate clinical relevance with methodological novelty, working with clinical microbiology at Aarhus University Hospital, which produces thousands of MALDI-MS samples per year, and with planned validation of models as new samples arrive. Key research directions include novel MS data representations (moving beyond binned spectra toward, e.g., audio spectrogram encodings or learned embeddings), explainable AI that translates model outputs into interpretable visualisations for clinical microbiologists and chemists, cross-platform generalisation to high-resolution MALDI (MALDI-2, timsTOF) and LC-MS, and biological extensions such as rare infections, fungal AMR, and sepsis applications. Two postdocs in the project contribute to each other's work and share co-first authorship across a joint publication pipeline.

Your job responsibilities will consist of:

• Independent research of high international quality, including publication.
• Developing and benchmarking deep learning models (PyTorch or equivalent) for AMR detection from MALDI-TOF mass spectrometry data, in collaboration with clinical microbiology at Aarhus University Hospital.
• Exploring novel MS data representations beyond binned spectra, such as audio spectrogram encodings or learned embeddings, and developing explainable AI methods that translate model outputs into interpretable visualisations for clinicians and chemists.
• Extending methods to high-resolution MALDI (MALDI-2, timsTOF) and LC-MS platforms available at Aarhus University.
• Collaborate with both university researchers, clinical researchers and two involved companies.
• Writing well-documented, reproducible code and contributing to open-source Python packages released alongside the methods papers, including close collaboration with the second postdoc on a shared publication pipeline.

You will report to the AIMS principal investigator: Associate Professor Palle Villesen.

You have academic qualifications at PhD level, for example within the following areas bioinformatics, data science, computer science, or another quantitative field, with a genuine interest in spectral data. You enjoy iterating on practical ideas, but do so in a structured, well-documented way that supports benchmarking, reproducibility, and reuse by others.

Essential:

• Strong data analysis and machine learning skills and experience with PyTorch (or equivalent frameworks).
• Hands-on experience with data representation and embeddings, ideally applied to spectral, time-series, or signal-like data.
• Comfort with Git/GitHub, structured project organisation, and writing code documented well enough to support benchmarking and Python package development.
• A pragmatic, iterative mindset – prioritising what works empirically and is testable over purely theoretical correctness.

Valued:

• Experience with high performance computing (HPC).
• Prior exposure to mass spectrometry, omics, audio, or other high-dimensional structured data.
• Interest in open-source software development; we plan to release Python packages alongside the methods papers and value contributions the wider community can build on.

As a person, you have good interpersonal skills, are inclusive and team-oriented and able to contribute to a good work environment. We expect you to be fluent in oral and written English.

In order to be assessed as qualified for a Postdoc position, you must meet these academic criteria.

Shortlisting will be used.

Your application must include the following:

• Motivated application
• Curriculum Vitae
• Diploma
• Template for applicant – postdoc
• A list of publications
• A teaching portfolio. We refer to Guideline on the use of teaching portfolios
• A maximum of five of the publications of greatest relevance to the job may be submitted (optional)
• Research plan can be uploaded (optional)
• Coauthor statement(s) can be uploaded (optional)
• References/recommendations can be uploaded separately in the e-recruitment system (optional)

We refer to the faculty's Guidelines for applicants. Aarhus University's ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants.

Aarhus University offers a broad variety of services for international researchers and accompanying families, including assistance with relocation and career counselling to expat partners. Please find more information about the International Staff Office and the range of services here. Aarhus University also has a Junior Researcher Association and offers career development support. You can read more about these resources here. The application must be submitted via Aarhus University's recruitment system, which can be accessed under the job advertisement on Aarhus University's website.