Postdoctoral Research Scientist

3 weeks ago


Leicester, Leicester, United Kingdom University Of Leicester Full time
Position Overview

The University of Leicester Ulverscroft Eye Unit (UEU) is pleased to announce an opening for a Postdoctoral Research Scientist (PDRA) role aimed at investigating the potential of retinal image-derived phenotypes in disease prediction and modeling.

Research Focus

This research initiative will involve genome-wide and phenome-wide association studies, in conjunction with the application of advanced deep learning techniques to imaging datasets.

Depending on the interests of the selected candidate, there may also be opportunities to participate in laboratory experiments, including CRISPR-Cas9 mutagenesis and retinal disease modeling.

Responsibilities

The PDRA will be tasked with co-developing and executing an independent original research program that aligns with the strategic priorities of the group. Responsibilities will also include managing extensive genotype and phenotype datasets, overseeing clinical studies, and providing support to research staff and PhD/iMSc/project students.

Research Environment

The UEU is a clinical research unit recognized for excellence in ophthalmic research.

UEU boasts state-of-the-art research facilities at the University Hospitals of Leicester and the Robert Kilpatrick Clinical Sciences Building, as well as exceptional laboratory facilities within a purpose-built animal research building.

The team consists of six full-time staff members with diverse expertise in clinical ophthalmology, genetics, imaging, engineering, electrophysiology, programming, eye tracking, and visual behavior.

Our team benefits from world-class data science infrastructure, including a High Performance Computing facility with dedicated research computing support and secure IT systems.

Additionally, the core team receives broader support from teams at the University Hospitals of Leicester, enhancing our research capabilities.

Candidate Profile

We are looking for a candidate with a robust background in bioinformatics, computational biology, or a closely related discipline.

The ideal candidate will be innovative and driven, possessing excellent communication skills and a strong interest in addressing complex challenges.

Experience in genetic data analysis and statistical genetics methodologies, such as GWAS and PheWAS, is essential.

Proficiency in statistical programming languages (e.g., R, Python) and a solid understanding of genetic and molecular biology concepts are also required.

Familiarity with CRISPR-Cas9 technology, as well as knowledge of artificial intelligence and machine learning techniques applied to biological datasets, would be particularly advantageous.

Research Opportunities

This position is situated within a dynamic research environment that provides access to cutting-edge computational and experimental resources.

Candidates will have the chance to engage in multidisciplinary projects that aim to bridge the gap between computational analysis and experimental biology, making significant contributions to the field of disease prediction and modeling through retinal image analysis.



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