Researcher in Statistical Genetics with interest in women’s health
At the Department of Gynaecology and Obstetrics, we’re passionate about making a real difference in women’s lives. Our team encompasses international researchers with specialized knowledge in biomarker discovery, placental biology, microbiome analysis, machine learning applications, and clinical data science all with the common goal to translate computational discoveries into improved diagnostic and therapeutic approaches for women’s health conditions.
Within this collaborative environment, you will contribute statistical genetics expertise to advance our understanding of complex reproductive health conditions. As a part of our team, you will: Identify causal relationships and genetic risk factors for complex diseases through large-scale analyses using Mendelian randomization, polygenic risk scoring, and other advanced statistical approaches across diverse genomic and epidemiological datasets.
Characterize disease-associated variation in challenging genomic regions including structural variants, copy number variations, and repetitive elements using whole genome sequencing data, moving beyond standard SNP-based approaches to capture the full spectrum of genetic variation contributing to disease risk.
Build comprehensive data integration frameworks that combine health records, genetic data, and epidemiological information from specialized Danish cohorts (e.g., Copenhagen Pregnancy Loss Study and Copenhagen Hospital Biobank), UK Biobank, and similar large-scale studies to enable novel discoveries.
Advance precision women’s health by creating robust, clinically relevant risk prediction models that integrate genetic ancestry, family history, and medical history to improve patient outcomes and inform personalized treatment strategies. Our team plays a crucial role in translating complex genomic, metabolomic, proteomic, and metagenomic data into actionable insights that directly improve disease risk assessment and causal understanding, thereby enabling the development of novel treatments.
You will have access to state-of-the-art computational resources, including the Danish national supercomputer for AI, Gefion, and opportunities for international collaboration and conference participation to advance your research career. Applications will be reviewed upon receipt, and interviews may be scheduled at any time, depending on applicant availability.Projected start date: As soon as possible Qualifications PhD degree in genetic epidemiology or statistical genetics, with proven track record of relevant scientific publications. 3+ years’ experience analyzing large genetic datasets (UK Biobank, All-of-Us, or similar cohort data, GWAS analysis, polygenic risk scoring, or similar).
Experience with causal inference methods, particularly Mendelian randomization and instrumental variable approaches, to facilitate robust causal inference from observational genetic data. Experience with whole-genome sequencing data Experience with working in a high-performance computing environment Familiarity with population genetics principles (population stratification and ancestry inference) Proficiency in Python or R, with experience in statistical analysis and genomic data manipulation.
Professional proficiency in English. Preferred, but not essential, Knowledge of basic concepts on gynecology, obstetrics, or reproductive physiology to facilitate effective collaboration with clinical researchers. Experience with variant calling pipelines and quality control procedures Experience with the UK Biobank Research Access Platform Proficient in git version control for collaborative code development and project management.The application should include a cover letter, curriculum vitae, and relevant diplomas. The position is full-time, 37 hours per week and is limited to a two-year period but can be extended. Terms of employment and salary Salary, pension and terms of employment will be in accordance with the agreement of academics employed in regions etc.
concluded between RLTN and DM, DJØF, IDA etc. For further information, contact Senior Researcher Karina Banasik (email karina.banasik@regionh.dk). Fakta Jobtype Statistiker Arbejdssted Hvidovre Hospital Arbejdstid 37 Jobnummer 264367 Ansøgningsfrist 17-10-2025 Contact [Project.ContactPerson1.ProfileImage-] Mette Harms Krøll Lægesekretær [Project.ContactPerson2.ProfileImage-] [Project.ContactPerson3.ProfileImage-] [Project.ContactPerson4.ProfileImage-] Om at bringe liv til verden, om at redde liv og forbedre livskvalitet.
På Amager og Hvidovre Hospital er der plads til dine ambitioner. Vi er eksperter i folkesygdomme og kan samtidig tilbyde højt specialiseret behandling til mennesker med sjældne sygdomme. Du bliver en del af et stærkt fagligt miljø, hvor vi udvikler og deler ny viden.Et miljø, hvor vi står klar med ekspertise og omsorg hele døgnet. Du får et arbejde, der giver mening, fordi det handler om liv. Fakta Amager og Hvidovre Hospital er et af landets største akuthospitaler Hospitalet har mere end 5.570 ansatte, som arbejder på tre forskellige matrikler Vi har 670.000 ambulante besøg og 91.000 indlæggelser hvert år Hospitalets fødeafdeling er landets største med 7.100 fødsler om året.