Marc Vaudel

Professor at University of Bergen

University of Bergen
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Positions (1)

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Marc Vaudel

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University of Bergen

The University of Bergen's Faculty of Medicine, Department of Clinical Science, invites applications for a fully funded four-year PhD position as part of the project “Temporary inconvenience or early warning signs? A new take on maternal symptoms in early pregnancy and their consequences.” This research opportunity is based at the Center for Diabetes Research, located at the Children and Youth Hospital in Bergen, Norway, and is funded by the University of Bergen. The project focuses on understanding the biological underpinnings and future health implications of maternal symptoms during early pregnancy, such as nausea, vomiting, bleeding, pain, and fatigue. The successful candidate will leverage the extensive Norwegian Mother, Father and Child Cohort Study, which contains detailed data on approximately 100,000 pregnancies. The research will employ advanced proteomics, utilizing mass spectrometry and biobank-scale data analysis, to investigate the association between protein abundance and pregnancy symptoms, and to explore whether proteomic patterns can predict later health outcomes for both mother and child. The position offers a dynamic and supportive research environment, with guidance and training provided, as well as opportunities for career development and international research exchanges. The role includes 25% mandatory departmental duties, such as teaching, exam work, or supervision, depending on departmental needs. Eligibility and Requirements: Applicants must hold a master’s degree or equivalent in medical data science, health information technology, or bioinformatics. Required qualifications include academic and practical experience in healthcare data science, experience with mass spectrometry-based proteomic bioinformatic pipelines, proficiency in at least one object-oriented compiled programming language (Java or C#) and one general-purpose programming language (R or Python), and fluency in oral and written English. Additional desirable skills include professional programming (version control, unit testing, continuous integration), experience with Linux, databases, and server-based computing. Applicants with foreign degrees must provide certified translations and a recognition review from the Norwegian Directorate for Higher Education and Skills (HK-dir). Admission to the University of Bergen’s PhD programme is mandatory. Funding and Benefits: The position is fully funded, with a starting salary of NOK 570,000 per year (higher for applicants with medical or dental qualifications), enrolment in the Norwegian Public Service Pension Fund, and access to excellent welfare benefits. The appointment is for a fixed term of four years, with the possibility of up to four months post-PhD completion if the degree is achieved in less than four years. Application Process: Applications must be submitted online via the JobbNorge portal. Required documents include a statement of research interests and motivation, certified copies of diplomas and transcripts, documentation of English language proficiency, a complete list of publications, and contact information for two references. Applicants with foreign degrees must submit a recognition review from HK-dir. The application deadline is 7th December 2025. For further information, contact Professor Marc Vaudel at [email protected] This position is an excellent opportunity for candidates interested in maternal health, proteomics, and data-driven biomedical research, offering a collaborative environment and strong institutional support at one of Europe’s leading universities.

10 months ago

Articles (1)

Background The nonrandom distribution of alleles of common genomic variants produces haplotypes, which are fundamental in medical and population genetic studies. Consequently, protein-coding genes with different co-occurring sets of alleles can encode different amino acid sequences: protein haplotypes. These protein haplotypes are present in biological samples and detectable by mass spectrometry, but they are not accounted for in proteomic searches. Consequently, the impact of haplotypic variation on the results of proteomic searches and the discoverability of peptides specific to haplotypes remain unknown. Findings Here, we study how common genetic haplotypes influence the proteomic search space and investigate the possibility to match peptides containing multiple amino acid substitutions to a publicly available data set of mass spectra. We found that for 12.42% of the discoverable amino acid substitutions encoded by common haplotypes, 2 or more substitutions may co-occur in the same peptide after tryptic digestion of the protein haplotypes. We identified 352 spectra that matched to such multivariant peptides, and out of the 4,582 amino acid substitutions identified, 6.37% were covered by multivariant peptides. However, the evaluation of the reliability of these matches remains challenging, suggesting that refined error rate estimation procedures are needed for such complex proteomic searches. Conclusions As these procedures become available and the ability to analyze protein haplotypes increases, we anticipate that proteomics will provide new information on the consequences of common variation, across tissues and time.

Year:

2022

Collaborators (1)

Bo Wen

Baylor College of Medicine

UNITED STATES
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