cfDNA Genomics Postdoc — Statistical & ML Methods

Wellcome Sanger Institute; Hinxton; Hybrid; GBP 39,000 - 50,000; Full time

Benefits offered by this job

Hybrid working

Career development opportunities

Job summary

The Wellcome Sanger Institute is seeking a Postdoctoral Fellow or Senior Postdoctoral Fellow to join the Martin group and advance statistical and machine learning methods for cell-free DNA from pregnant women and people.

You will develop and apply analyses to study fetal genomes and placental biology at scale, collaborating with teams across Europe to identify biomarkers for pregnancy complications and contributions to neonatal genomics projects.

Qualifications

• PhD in statistics, statistics genetics, or related field.
• Strong background in statistics or statistical genetics.
• Experience working with raw sequence data (alignments, variant calling, QC).
• Experience analysing large-scale human genetic/genomic data.
• Proficiency in Python and/or R, and Unix/Linux.
• Experience using AI tools to improve productivity in research.
• Knowledge of statistical methods for large-scale genetic research.
• Experience writing reproducible code with GitHub, Snakemake/Nextflow, RMarkdown.
• Experience developing pipelines/software for large-scale genomic analyses on HPC/cloud.
• Creativity, enthusiasm, collaboration.

Responsibilities

• Develop statistical and deep learning methods for calling fetal and maternal genotypes from high-coverage sequence data on cfDNA.
• Apply methods to study pregnancy complications in large cohorts.
• Develop biomarkers from methylation-aware whole-genome cfDNA data.
• Collaborate with groups at the Norwegian Institute of Public Health and the University of Helsinki and others.

Skills

PhD in statistics

Statistical genetics

Genomics

Bioinformatics

Machine learning

Python

R

Unix/Linux

GitHub

Snakemake/Nextflow

RMarkdown

HPC

Education

PhD required

Tools

GitHub

Snakemake/Nextflow

RMarkdown

Job description

The Wellcome Sanger Institute is seeking a Postdoctoral Fellow or Senior Postdoctoral Fellow to join the Martin group and advance statistical and machine learning methods for cell-free DNA from pregnant women and people.

You will develop and apply analyses to study fetal genomes and placental biology at scale, collaborating with teams across Europe to identify biomarkers for pregnancy complications and contributions to neonatal genomics projects.