Postdoctoral Fellow – Early-Life Genomics & Multi-omics (Martin Group) – Wellcome Sanger Institute

Job Description

The Martin group at the Wellcome Sanger Institute is seeking a highly motivated and creative Postdoctoral Fellow to work towards understanding the genetic basis of early-life traits and conditions, and/or to develop biomarkers for pregnancy complications and neonatal diseases.

The group works on the genetic basis of rare and common disease using large-scale human genetic datasets linked to electronic health records and questionnaires, with emphasis on neurodevelopmental disorders, complex disease in populations with high consanguinity, and germline mutation rates. It is now building a programme spanning pregnancy loss, fetal growth restriction and complications of premature birth, including large-scale sequencing of birth cohorts, multi-omic studies of neonatal conditions using nationwide Scandinavian dried blood spots, and sequencing of cell-free DNA (cfDNA) from pregnant mothers.

The postdoc will work on one or more of these projects, which can be tailored to the postdoc's interests and expertise, in collaboration with groups in the UK, Scandinavia and elsewhere.

Key Responsibilities

• Analyse large-scale proteomic data from nationwide Scandinavian dried blood spots to develop biomarkers for neonatal conditions common in premature babies
• Analyse new sequence and genotype data from over 110,000 individuals across four birth cohorts, including the Norwegian MoBa cohort, to explore genetic influences on neurodevelopmental and perinatal traits
• Disentangle direct from indirect genetic effects and explore time-varying genetic effects using longitudinal data
• Explore factors influencing penetrance of variants associated with rare neurodevelopmental conditions
• Develop biomarkers for pregnancy complications from methylation-aware whole-genome sequencing of cfDNA

Qualifications

• PhD in statistics, statistical genetics, genetics, genomics, proteomics, bioinformatics or similar
• Experience analysing large-scale high-throughput human genetic, epigenetic and/or proteomic data, including QC and normalisation

Experience

Experience in statistical analyses of large-scale human genetic or other omic datasets, particularly DNA sequence, methylation and/or high-throughput proteomic data.

Skills Required

• Statistical methods for large-scale omics
• Python and/or R, Unix/Linux
• Reproducible code (GitHub, Snakemake/Nextflow, RMarkdown)
• Experience or enthusiasm for AI tools in research
• Ability to work independently and supervise less experienced scientists
• Strong communication and problem-solving skills

Additional Information

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