Senior Research Associate in Molecular Epidemiology

The role

We are seeking a talented postdoctoral researcher with experience in Epidemiology and omics. You will be responsible for conducting and disseminating high-quality translational research concerned with the impact of infertility and its treatment with Assisted Reproductive Technology (ART) or Medically assisted reproduction (MAR) on molecular mechanisms, using epigenomic, transcriptomics, metabolomic and proteomic data.

Why Join Us:

• Work on impactful research related to infertility and its treatment.
• Be part of a cohesive, friendly, and diverse team.
• Work in an interdisciplinary and international environment.

What will you be doing?

• Conducting research to advance understanding of the effects of infertility and its treatment (ART and MAR) on epigenomic, transcriptomics, metabolomic and proteomic pathways) and the extent to which any of these molecular mechanisms mediate effects of infertility, ART / MAR on parental and offspring future health.
• Generating research ideas, developing and executing analysis plans that triangulate evidence from different approaches to support causal analyses
• Identifying relevant data sources and bioinformatic tools
• Cleaning and analyse large-scale, high-dimensional datasets
• Presenting research findings at local, national, and international meetings and conferences

You should apply if

Essential

• A relevant postgraduate research degree- i.e. a PhD (or working towards one) in epidemiology, molecular epidemiology, medical statistics, or a related quantitative discipline, or equivalent professional experience
• Expertise in Epidemiology
• Experience in analysing high dimensional ‘omics (e.g. metabolomics, proteomics) data in large cohorts
• Expertise in using standard statistical methods (e.g. regression models)
• expertise in performing causal inference analyses (e.g. Mendelian randomization, within family analyses, using negative and/or positive controls), including understanding analysis assumptions and ability to explore these with sensitivity analyses
• Expertise using R, Python or other common languages
• Excellent verbal and written communication skills

Desirable

• Experience with high-performance computing on a cluster
• Experience of developing/sharing open-source code
• Experience in reproductive Epidemiology

Publications involving ‘omics data and/or causal methods (Mendelian randomization, within family and using negative controls)

Additional information

Contract type: Open-ended with funding until 21/11/2026

Work pattern: Full time/1 FTE (part-time considered)

School/Unit: Bristol Medical School

Shift pattern: 35 hours per week (part-time considered)

This advert will close at 23:59 UK time on 28/10/2024

For informal queries please contact:

Professor Deborah A Lawlor (d.a.lawlor@bristol.ac.uk)

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