Postdoc: ML for Proteomics & Peptide Fragmentation

Cph Ai Hub; Odense; Hybrid; DKK 550,000 - 730,000; Full time

Job summary

The Department of Biochemistry and Molecular Biology at the University of Southern Denmark in Odense invites applications for a postdoctoral position at the interface of computational proteomics, ML, and mass spectrometry. You will join the Protein Research Group to develop data-driven fragmentation models using large curated MS/MS datasets.

We seek candidates with a PhD in a relevant field and strong ML experience who can work independently and collaborate with experimental colleagues.

Qualifications

• PhD in computational proteomics, bioinformatics, ML, CS, chemometrics, analytical chemistry, or related field.
• Strong experience in ML/DL applied to complex scientific datasets.
• Ability to independently design, implement, evaluate, and document computational solutions.
• Proficiency in Python and ML/data science frameworks.
• Experience with preprocessing, curation, and QC of large datasets.
• Analytical mindset and ability to work independently on computational problems.
• Interest in computation, chemistry, and mass spectrometry.

Responsibilities

• Develop computational and ML workflows for large-scale MS/MS data analysis.
• Collaborate with experimental researchers generating MS data for model development.
• Extend models to cover peptide fragmentation and related PTMs.
• Create reproducible and well-documented pipelines and data structures.

Skills

Machine Learning

Python

Independent Research

Data Preprocessing

Analytical Mindset

Interdisciplinary Interest

Education

PhD in relevant field

Job description

The Department of Biochemistry and Molecular Biology at the University of Southern Denmark in Odense invites applications for a postdoctoral position at the interface of computational proteomics, ML, and mass spectrometry. You will join the Protein Research Group to develop data-driven fragmentation models using large curated MS/MS datasets.

We seek candidates with a PhD in a relevant field and strong ML experience who can work independently and collaborate with experimental colleagues.