Postdoctoral Researcher in Computational Proteomics and Machine Learning

University of Southern Denmark - SDU; Odense; On-site; DKK 480,000 - 600,000; Full time

Benefits offered by this job

Pension plan

International collaboration

Job summary

The University of Southern Denmark invites applications for a postdoctoral position at the interface of computational proteomics, machine learning, and mass spectrometry. You will develop ML workflows for large-scale tandem MS data and work closely with experimental colleagues to advance peptide fragmentation analysis.

Located in Odense, the Protein Research Group offers an interactive environment and access to state-of-the-art MS platforms.

Qualifications

• PhD in computational proteomics, bioinformatics, machine learning, computer science, chemometrics, analytical chemistry, or closely related field.
• Strong experience in machine learning and/or deep learning applied to complex scientific datasets.
• Proficiency in Python and relevant machine learning/data science frameworks.
• Experience with data preprocessing, curation, and quality control for large and complex datasets.

Responsibilities

• 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 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.
• Investigate how models may help reveal fragmentation trends and chemically meaningful patterns in large-scale MS/MS datasets.
• Work independently on model development and implementation while interacting closely with experimental researchers.
• Disseminate findings through peer-reviewed publications, conference presentations, and open scientific resources.

Skills

Machine learning

Python

Independent problem solving

Data preprocessing

Analytical mindset

Interdisciplinary collaboration

Mass spectrometry knowledge

Education

PhD in computational proteomics or related field

Tools

TensorFlow/PyTorch

MS/MS data analysis tools

Job description

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 metricsContribute 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.

Contact Information

For further information, please contact: Prof. Frank Kjeldsen, Department of Biochemistry and Molecular Biology, University of Southern Denmark, [e-mail]

Application, salary etc.

The successful applicant will be employed in accordance with the agreement between the Ministry of Finance and AC (the Danish Confederation of Professional Associations). Please check links for more information on salary (only available in Danish) and taxation.

Salary is determined in accordance with the applicable collective agreement and based on objective and gender-neutral criteria, including the content of the position, responsibilities, and qualification requirements.
As an applicant, you are entitled to information about the starting salary and salary range for the position. This information will be provided during the recruitment process. SDU does not collect information on applicants’ previous salary.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

About SDU

The University of Southern Denmark was established to create value for and with society. Whether our contributions come in the form of excellent research, innovative solutions, education or learning, we must make a positive difference to society and contribute to a sustainable future. We do this by cultivating talents and creating the best environments for research and learning. It is therefore crucial that SDU retains, develops and recruits talent. At the same time, we need to ensure consistently high quality in all our activities – and we can only do that with the right people. The University’s researchers, lecturers, students, managers and technical/administrative staff are the foundation of our success.