{"id":2268396,"url":"https://alion.io/job/sdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning","title":"Postdoctoral Researcher in Computational Proteomics and Machine Learning","company":{"id":38829,"name":"University of Southern Denmark","domain":"sdu.dk","url":"https://alion.io/company/sdu","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Odense, Denmark"],"countries":["DK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Explainable AI","optional":true},{"name":"Interpretability","optional":true}],"status":"live","first_seen_at":"2026-10-05T11:47:37Z","employer_posted_date":"2026-10-05","last_verified_at":"2026-10-24T14:16:44Z","board_verified":true,"closed_at":null,"days_open":19,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":19},"description":"Department of Biochemistry and Molecular Biology, University of Southern Denmark\nLocation: Odense, Denmark\nDuration: 2 years, with the possibility of a 1-year extension\nStarting Date: 1 January 2027, or as soon as possible thereafter\nProject Description\nWe 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.\nThe 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.\nThe 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.\nResearch Environment and Collaborative Structure\nThe 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.\nThe 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.\nResponsibilities\nThe postdoctoral researcher will be expected to:\nDevelop computational and machine learning workflows for large-scale analysis of tandem mass spectrometry data \nContribute to the structuring, curation, and quality control of large experimental MS/MS datasets \nBuild data-driven models for peptide fragmentation analysis using experimentally generated spectra \nIntegrate relevant variables such as peptide sequence, precursor charge state, collision energy, and peptide modifications into computational frameworks \nEvaluate model performance using suitable similarity, quality, and generalization metrics \nContribute to the extension of computational models toward chemically and biologically relevant peptide classes, including selected post-translational modifications \nInvestigate how computational models may help reveal fragmentation trends and chemically meaningful patterns in large-scale MS/MS datasets \nWork independently on model development, implementation, and computational problem solving, while interacting closely with experimental researchers in the group \nContribute to reproducible and well-documented computational pipelines, data structures, and analysis workflows \nDisseminate findings through peer-reviewed publications, conference presentations, and open scientific resources where relevant \nRequired Qualifications\nApplicants must have:\nA PhD in computational proteomics, bioinformatics, machine learning, computer science, chemometrics, analytical chemistry, or a closely related field \nStrong experience in machine learning and/or deep learning applied to complex scientific datasets \nDemonstrated ability to independently develop computational solutions, including model design, implementation, evaluation, and documentation \nProficiency in Python and relevant machine learning/data science frameworks \nExperience with data preprocessing, curation, and quality control for large and complex datasets \nA strong analytical mindset and the ability to work independently on computational research problems \nInterest in working at the interface of computation, chemistry, and mass spectrometry \nDesirable Qualifications\nThe following qualifications will be considered an advantage:\nExperience with mass spectrometry-based proteomics, computational mass spectrometry, or peptide fragmentation-related data analysis \nExperience with neural network architectures relevant for sequence-based prediction tasks \nExperience with model interpretability, explainable AI, or feature analysis in scientific machine learning \nInterest in peptide chemistry, gas-phase ion behavior, or post-translational modifications \nExperience with reproducible workflows, FAIR data principles, and scalable computational pipelines \nAbility to collaborate effectively across computational and experimental disciplines \nWhat We Offer\nA unique opportunity to work at the intersection of proteomics, mass spectrometry, and machine learning on scientifically ambitious and methodologically innovative research\nThe opportunity to develop computational methods for experimentally generated high-quality tandem mass spectrometry data \nA central and independent role in shaping the computational direction of a new research effort \nClose collaboration with experimental researchers working on peptide ionization, fragmentation, and advanced LC-MS/MS method development \nA strong interdisciplinary research environment with expertise spanning proteomics, biological mass spectrometry, peptide chemistry, and data analysis \nAccess to state-of-the-art mass spectrometry platforms and large in-house datasets \nAn international and collaborative research culture with opportunities for scientific development, publication, and conference participation \nCompetitive salary and benefits according to Danish collective agreements, including pension and support for international candidates where relevant \nAbout the Protein Research Group\nThe 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.\nLocated 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.\nContact Information\nFor further information, please contact: Prof. Frank Kjeldsen, Department of Biochemistry and Molecular Biology, University of Southern Denmark, \nApplication, salary etc.\nThe 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.\nSalary 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.\nAs 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.\nApplications must include:\nA motivation letter describing the applicant’s interest in the position and relevant qualifications \nCurriculum vitae \nCopies of degree certificates and transcripts \nContact information for relevant references/recommendation letters\nShortlisting may be used in the assessment process. Incomplete applications and applications received after the deadline will neither be considered nor evaluated.\nTo qualify you must have passed a PhD or equivalent. Applications will be assessed by an expert assessor/committee. Applicants will be informed of their assessment by the university.\nThe University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.\nApplications must be submitted electronically using the link \"Apply now\". Attached files must be in Adobe PDF format. We strongly recommend that you read How to apply for a position at SDU before you apply.\nIf you experience technical problems, please contact \nFurther information for international applicants about entering and working in Denmark.\nAbout SDU\nThe 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.","description_format":"text","description_chars":9446,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Denmark","iso":"DK","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Bioinformatics","Health Care","Higher Education"],"lifecycle":[{"event":"open","at":"2026-10-11T07:19:36Z"}],"visa":[],"liveness":{"score":66,"band":"ok","label":"Likely open","p_open":1,"p_active":0.738,"p_room":0.9,"age_days":18,"expected_fill_days":27,"reasons":["conf:5","velocity","win:mid"],"computed_at":"2026-10-24T06:02:35Z"},"pay":null,"html_url":"https://alion.io/job/sdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning","json_url":"https://alion.io/job/sdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning.json","meta":{"generated_at":"2026-10-24T16:37:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":24056,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-25T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":38829},"rest":"https://alion.io/mcp/rest/get_company?id=38829"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fsdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fsdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fsdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/sdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fsdu-postdoctoral-researcher-in-computational-proteomics-and-machine-learning"}]}