cfDNA Genomics Postdoc: Advanced Statistical & ML Methods

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

Benefits offered by this job

Hybrid working

Job summary

The Wellcome Sanger Institute seeks a Postdoctoral Fellow or Senior Postdoctoral Fellow to develop statistical and machine learning methods for cell-free DNA from pregnant women and people. You will build and apply methods to fetal/metal genotypes, explore epigenetic data, and drive collaborative projects across large cohorts.

Ideal candidates have a strong statistics background, experience with sequencing data, and excellent software development skills.

Qualifications

• PhD in statistics or statistical genetics or related field.
• Strong background in statistics with ability to develop and benchmark new methods.
• Experience with raw sequence data and quality control.
• Experience analysing large-scale genetic/genomic data.
• Python and/or R proficiency, Unix/Linux.
• Interest in using AI tools to enhance research productivity.
• Experience in coding with reproducible workflows and GitHub.

Responsibilities

• Develop statistical and deep learning methods for cfDNA analysis.
• Apply methods to study pregnancy complications in large cohorts.
• Collaborate with international groups on epigenetic and genetic data.

Skills

PhD in stats

Statistics/Genetics

Python & R

Unix/Linux

AI in research

Genomics data

Reproducible code

Workflow automation

Collaboration

Education

PhD in statistics/genetics

Tools

Snakemake/Nextflow

GitHub

HPC/Cloud

Job description

The Wellcome Sanger Institute seeks a Postdoctoral Fellow or Senior Postdoctoral Fellow to develop statistical and machine learning methods for cell-free DNA from pregnant women and people. You will build and apply methods to fetal/metal genotypes, explore epigenetic data, and drive collaborative projects across large cohorts.

Ideal candidates have a strong statistics background, experience with sequencing data, and excellent software development skills.