Research Assistant in Statistical Genetics
| Dyddiad hysbysebu: | 16 Gorffennaf 2025 |
|---|---|
| Cyflog: | £34,982 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 30 Gorffennaf 2025 |
| Lleoliad: | Kennedy Institute of Rheumatology, Roosevelt Drive, Headington, Oxford OX3 7FY |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | University of Oxford, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences |
| Math o swydd: | Dros dro |
| Cyfeirnod swydd: | 180932 |
Crynodeb
We are seeking a Research Assistant with a strong interest in statistical genetics, proteomics and immune regulation to support an interdisciplinary project investigating how genetic variation within the MHC region influences plasma protein levels.
In this role, you will work independently on assigned research tasks and report progress, challenges, and outcomes to project supervisors and group leads. You will perform quality control, processing, and statistical analysis of large-scale genetic (genotyping) and proteomic (Olink) datasets from the UK Biobank and China Kadoorie Biobank. You will be responsible for conducting comparative analyses to identify shared and ancestry-specific variant–protein associations across cohorts, as well as generating and interpreting high-quality visualisations of complex pQTL data, such as Manhattan plots, concordance scatter plots and Miami plots. You will also apply advanced statistical genetics methods, including meta-analysis using PLINK 1.9 (fixed-effects inverse-variance model), conditional analysis using REGENIE, and fine-mapping of HLA–protein associations.
You must hold a first degree in Genomic Medicine, Statistical Genetics, Bioinformatics, Computational Biology, or a related quantitative discipline. You will also demonstrate a proficiency in statistical programming using R and/or Python, with experience in data management, analysis, and visualisation. You will demonstrate experience working with large-scale biological datasets, preferably from biobank studies (e.g., UK Biobank, China Kadoorie Biobank) as well as a solid understanding of statistical genetics concepts, including GWAS, pQTLs, linkage disequilibrium, fine-mapping and meta-analysis. Practical experience with genetic association testing and related workflows alongside a familiarity with command-line environments, high-performance computing (HPC) environments and pipeline execution on compute clusters (e.g., SLURM) are essential.
A master’s degree in Genomic Medicine, Statistical Genetics, Bioinformatics, Computational Biology, or a related quantitative discipline and prior experience or strong interest in immunology, particularly the Human Leukocyte Antigen (HLA) system are desirable.
Due to the nature of the research at the Kennedy Institute of Rheumatology, this job will require additional security pre-employment checks:
• A satisfactory basic Disclosure and Barring Service check
The closing date for applications is 12 noon on 30 July 2025. Applications for this vacancy are to be made online. You will be required to upload a CV and supporting statement as part of your online application. Please quote 180932 in all correspondence.
In this role, you will work independently on assigned research tasks and report progress, challenges, and outcomes to project supervisors and group leads. You will perform quality control, processing, and statistical analysis of large-scale genetic (genotyping) and proteomic (Olink) datasets from the UK Biobank and China Kadoorie Biobank. You will be responsible for conducting comparative analyses to identify shared and ancestry-specific variant–protein associations across cohorts, as well as generating and interpreting high-quality visualisations of complex pQTL data, such as Manhattan plots, concordance scatter plots and Miami plots. You will also apply advanced statistical genetics methods, including meta-analysis using PLINK 1.9 (fixed-effects inverse-variance model), conditional analysis using REGENIE, and fine-mapping of HLA–protein associations.
You must hold a first degree in Genomic Medicine, Statistical Genetics, Bioinformatics, Computational Biology, or a related quantitative discipline. You will also demonstrate a proficiency in statistical programming using R and/or Python, with experience in data management, analysis, and visualisation. You will demonstrate experience working with large-scale biological datasets, preferably from biobank studies (e.g., UK Biobank, China Kadoorie Biobank) as well as a solid understanding of statistical genetics concepts, including GWAS, pQTLs, linkage disequilibrium, fine-mapping and meta-analysis. Practical experience with genetic association testing and related workflows alongside a familiarity with command-line environments, high-performance computing (HPC) environments and pipeline execution on compute clusters (e.g., SLURM) are essential.
A master’s degree in Genomic Medicine, Statistical Genetics, Bioinformatics, Computational Biology, or a related quantitative discipline and prior experience or strong interest in immunology, particularly the Human Leukocyte Antigen (HLA) system are desirable.
Due to the nature of the research at the Kennedy Institute of Rheumatology, this job will require additional security pre-employment checks:
• A satisfactory basic Disclosure and Barring Service check
The closing date for applications is 12 noon on 30 July 2025. Applications for this vacancy are to be made online. You will be required to upload a CV and supporting statement as part of your online application. Please quote 180932 in all correspondence.