Postdoctoral Researcher in Computational Proteomics and Machine Learning

Department of Biochemistry and Molecular Biology, University of Southern Denmark Location: Odense, Denmark Duration: 2 years, with the possibility of a 1-year extension Starting Date: 1 January 2027, or as soon as possible thereafter

Project Description We invite applications for a postdoctoral position at the interface of computational proteomics, machine learning, and mass spectrometry. The successful candidate will join a pioneering research program focused on peptide ionization and fragmentation in LC-MS/MS, with the aim of developing new computational approaches for peptide fragmentation analysis. The project centers on large-scale, experimentally curated tandem mass spectrometry datasets and the development of new computational strategies for fragmentation analysis under analytically underexplored conditions. It relies on modern machine learning approaches to model fragmentation behavior, support spectral interpretation, and enable future advances in peptide identification workflows. The position is embedded in the Protein Research Group (PRG) at the University of Southern Denmark, an internationally recognized environment in proteomics and biological mass spectrometry. The postdoctoral researcher will work in close collaboration with experimental colleagues generating high-quality tandem MS data for computational development. Research Environment and Collaborative Structure The Protein Research Group comprises eight PI-led teams and more than 50 researchers and students, offering a highly interactive and interdisciplinary research environment. The successful candidate will play a central role in the computational arm of the project and will collaborate closely with experimental researchers developing new mass spectrometric methods and generating large-scale fragmentation datasets. The position offers substantial scientific independence and the opportunity to help shape a new research direction at the intersection of machine learning, peptide chemistry, and proteomics. Responsibilities The postdoctoral researcher will be expected to: Develop computational and machine learning workflows for large-scale analysis of tandem mass spectrometry data

Contribute to the structuring, curation, and quality control of large experimental MS/MS datasets

Build data-driven models for peptide fragmentation analysis using experimentally generated spectra

Integrate relevant variables such as peptide sequence, precursor charge state, collision energy, and peptide modifications into computational frameworks

Evaluate model performance using suitable similarity, quality, and generalization metrics

Contribute to the extension of computational models toward chemically and biologically relevant peptide classes, including selected post-translational modifications

Investigate how computational models may help reveal fragmentation trends and chemically meaningful patterns in large-scale MS/MS datasets

Work independently on model development, implementation, and computational problem solving, while interacting closely with experimental researchers in the group

Contribute to reproducible and well-documented computational pipelines, data structures, and analysis workflows

Disseminate findings through peer-reviewed publications, conference presentations, and open scientific resources where relevant

Required Qualifications Applicants must have: A PhD in computational proteomics, bioinformatics, machine learning, computer science, chemometrics, analytical chemistry, or a closely related field

Strong experience in machine learning and/or deep learning applied to complex scientific datasets

Demonstrated ability to independently develop computational solutions, including model design, implementation, evaluation, and documentation

Proficiency in Python and relevant machine learning/data science frameworks

Experience with data preprocessing, curation, and quality control for large and complex datasets

A strong analytical mindset and the ability to work independently on computational research problems

Interest in working at the interface of computation, chemistry, and mass spectrometry

Desirable Qualifications The following qualifications will be considered an advantage: Experience with mass spectrometry-based proteomics, computational mass spectrometry, or peptide fragmentation-related data analysis

Experience with neural network architectures relevant for sequence-based prediction tasks

Experience with model interpretability, explainable AI, or feature analysis in scientific machine learning

Interest in peptide chemistry, gas-phase ion behavior, or post-translational modifications

Experience with reproducible workflows, FAIR data principles, and scalable computational pipelines

Ability to collaborate effectively across computational and experimental disciplines

What We Offer A unique opportunity to work at the intersection of proteomics, mass spectrometry, and machine learning on scientifically ambitious and methodologically innovative research The opportunity to develop computational methods for experimentally generated high-quality tandem mass spectrometry data

A central and independent role in shaping the computational direction of a new research effort

Close collaboration with experimental researchers working on peptide ionization, fragmentation, and advanced LC-MS/MS method development

A strong interdisciplinary research environment with expertise spanning proteomics, biological mass spectrometry, peptide chemistry, and data analysis

Access to state-of-the-art mass spectrometry platforms and large in-house datasets

An international and collaborative research culture with opportunities for scientific development, publication, and conference participation

Competitive salary and benefits according to Danish collective agreements, including pension and support for international candidates where relevant

About the Protein Research Group The Protein Research Group at SDU is internationally recognized for pioneering work in biological mass spectrometry, peptide and protein chemistry, gas-phase chemistry, and proteomics. Research in the group spans fundamental analytical chemistry, method development, structural biology, post-translational modifications, and translational applications in biomedicine and biotechnology. Located in Odense, the group offers an open, collaborative, and ambitious research environment with a strong emphasis on scientific rigor, interdisciplinary exchange, and long-term platform building. The successful candidate will join a setting in which computational and experimental researchers work in close interaction. Application deadline: 16. November 2026 at 23:59 hours local Danish time. Please see the full call, including how to apply, on www.sdu.dk