PhD: Decode Fat Distribution with Genomics & iPSC

University of Exeter; Exeter; On-site; GBP 20,000 - 24,000; Full time

Benefits offered by this job

Stipend provided

Job summary

University of Exeter researchers are leading an interdisciplinary studentship combining computational genomics with experimental biology to study fat distribution. The project integrates population genetics, regulatory genomics, and iPSC-derived adipocytes, with CRISPR-based perturbations to test causal variants.

The partnership with Cambridge provides access to advanced stem-cell facilities and high-content assays, supported by EPSRC funding.

Qualifications

• Experience analyzing whole-genome sequencing data.
• Background in computational genomics or population genetics.
• Experience with iPSC-derived adipocytes and CRISPR-based experiments.
• Ability to collaborate across Exeter and Cambridge facilities.

Responsibilities

• Identify coding and non-coding variants associated with fat distribution using WGS data across diverse cohorts.
• Integrate genetic signals with multi-omic maps and AI predictions to prioritize regulatory elements and genes.
• Establish human iPSC-derived adipocyte models patterned toward visceral and subcutaneous adipocytes.
• Quantify functional impact of prioritized genes and variants using CRISPR perturbations.

Skills

Computational genomics

Population genetics

Data analysis

Tools

CRISPR-Cas9

iPSC technology

AlphaGenome AI

DNANexus

Job description

University of Exeter researchers are leading an interdisciplinary studentship combining computational genomics with experimental biology to study fat distribution. The project integrates population genetics, regulatory genomics, and iPSC-derived adipocytes, with CRISPR-based perturbations to test causal variants.

The partnership with Cambridge provides access to advanced stem-cell facilities and high-content assays, supported by EPSRC funding.