Ph.D. Opportunity: Genetics of Pediatric Orthopedic Disorders

Genetics of Pediatric Orthopedic Disorders

We are seeking a highly motivated Ph.D. candidate to join our research project on the genetics of pediatric orthopedic disorders, with a primary focus on developmental dysplasia of the hip (DDH) and related conditions, including secondary osteoarthritis. This project aims to elucidate the genetic factors contributing to these disorders, leveraging large-scale genomic datasets and advanced bioinformatics methodologies. The project is a part of the work of the HIPS research group (www.uib.no/en/HIPS).

Key Responsibilities:

• Conduct genome-wide association studies (GWAS) to identify genetic variants associated with DDH and related conditions.
• Perform quality control analyses using tools such as PLINK (plink) and eigenvector analysis to account for population stratification (PCA and population stratification).
• Use statistical tools including the SAIGE R package (SAIGE documentation) for large-scale association testing.
• Perform functional follow-up analyses using online platforms and databases for epigenetic, transcriptomic, and gene expression data, such as:
  • GTEx for tissue-specific gene expression (gtexportal.org)
  • EWAS Atlas for methylation-associated traits (ngdc.cncb.ac.cn/ewas)
  • GeneHancer / GeneCards for regulatory elements (genecards.org)
  • Enrichr or g:Profiler for pathway and enrichment analysis (maayanlab.cloud/Enrichr, biit.cs.ut.ee/gprofiler)
• Manage and analyze data within secure computing environments, specifically the Tjenester for Sensitive Data (TSD) platform (TSD at UiO).

Datasets:

This research will utilize data from:

• The Norwegian Mother, Father and Child Cohort Study (MoBa) (FHI)
• The Trøndelag Health Study (HUNT) (NTNU)
• UK Biobank (UK Biobank)

Qualifications:

• Master’s degree in bioinformatics, computational biology, medicine, biology, microbiology, or a related field.
• Proficiency in programming languages such as Python and R.
• Familiarity with genomic analysis tools (PLINK, SAIGE) and statistical techniques for large-scale data.
• Experience or strong interest in functional analysis of genetic variants using transcriptomic, epigenomic, or expression data.
• Ability to work within secure environments and handle sensitive data.

Application Process:

This position is contingent upon the approval of funding from Helse Vest in September 2025. We are currently seeking a candidate to be named in the application. Interested individuals should submit a CV and a brief statement of interest outlining their experience and motivation. The job can either be fully remote or hybrid with either Bergen or Førde.

For more information, please contact Kaya Kvarme Jacobsen at kaya.kvarme.jacobsen@gmail.com.