Senior Research Associate in Molecular Epidemiology

We are seeking a talented postdoctoral researcher with experience in Epidemiology and human genetics research. You will be responsible for conducting and disseminating high-quality translational research concerned with improving the evidence base for the prevention and treatment of pregnancy-related complications, such as miscarriages, gestational diabetes, preeclampsia, preterm birth and perinatal depression. In particular, this post will involve integrating common and rare genetic variants to (i) transform the current understanding of molecular pathways leading to pregnancy complications and (ii) identify potential drug targets to manage these conditions. You will be part of a cohesive, friendly and diverse team working within the MR-PREG collaboration, including data for > 400,000 mothers on clinical outcomes, genetics, and other omics (i.e. DNA methylation, proteomics, metabolomics, and placenta transcriptomics in subsets of participants). In addition, you will closely engage with several international partners, particularly Prof. Frayling (University of Geneva), Assoc. Prof. Kutalik (University of Lausanne), Prof. Evans (University of Queensland) and Dr. Moen (University of Oslo).  For more information, please contact Carolina Borges ([email protected]).

Research Responsibilities

• Conduct research using rare and common genetic variants to improve knowledge on molecular mechanisms of pregnancy-related complications
• Generate ideas, develop and execute analysis plans
• Identify relevant data sources and bioinformatic tools
• Clean and analyse large-scale, high-dimensional datasets
• Develop analytical tools, pipelines, and repositories for use in their own work and of the group
• Write scientific papers for peer reviewed journals
• Present research findings at local, national, and international meetings and conferences
• Contribute with supervision of PhD students

Administration Responsibilities

• Thorough documentation and version control of all code developed
• Preparation, annotation and documentation of datasets
• Engagement and collaboration with researchers within the IEU and externally
• Assist with the organisation of meetings linked to the IEU

Essential

Experience in Epidemiology, standard statistical methods (e.g. regression models), performing analyses for genome-wide association studies (GWAS), using Linux/Unix operating systems, using R, Python or other common languages, and liaising with external collaborators

Desirable

Experience analysing exome or whole genome sequencing data, genotype calling and imputation of genotyping array data, additional ‘omics data (i.e. DNA methylation, transcriptomics, proteomics, metabolomics). Experience of using high-performance computing on a cluster, developing/sharing open-source code. Previous publications involving GWAS and analyses of exome or whole genome sequencing data.

Contract type: Open-ended with funding until 30/10/2026 initially

Work pattern: Full time/ 1 FTE

Grade: Grade J/ (Pathway 2)

Salary: £41,732 - £46,974 per annum depending on previous experience

School/Unit: Bristol Medical School

Shift pattern: 35 hours per week

This advert will close at 23:59 GMT on29/02/2024

For informal queries please contact: Dr Carolina Borges ([email protected] )

We recently launched our strategy  to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.

We are seeking a talented postdoctoral researcher with experience in Epidemiology and human genetics research. You will be responsible for conducting and disseminating high-quality translational research concerned with improving the evidence base for the prevention and treatment of pregnancy-related complications, such as miscarriages, gestational diabetes, preeclampsia, preterm birth and perinatal depression. In particular, this post will involve integrating common and rare genetic variants to (i) transform the current understanding of molecular pathways leading to pregnancy complications and (ii) identify potential drug targets to manage these conditions. You will be part of a cohesive, friendly and diverse team working within the MR-PREG collaboration, including data for > 400,000 mothers on clinical outcomes, genetics, and other omics (i.e. DNA methylation, proteomics, metabolomics, and placenta transcriptomics in subsets of participants). In addition, you will closely engage with several international partners, particularly Prof. Frayling (University of Geneva), Assoc. Prof. Kutalik (University of Lausanne), Prof. Evans (University of Queensland) and Dr. Moen (University of Oslo).  For more information, please contact Carolina Borges ([email protected]).

Research Responsibilities

• Conduct research using rare and common genetic variants to improve knowledge on molecular mechanisms of pregnancy-related complications
• Generate ideas, develop and execute analysis plans
• Identify relevant data sources and bioinformatic tools
• Clean and analyse large-scale, high-dimensional datasets
• Develop analytical tools, pipelines, and repositories for use in their own work and of the group
• Write scientific papers for peer reviewed journals
• Present research findings at local, national, and international meetings and conferences
• Contribute with supervision of PhD students

Administration Responsibilities

• Thorough documentation and version control of all code developed
• Preparation, annotation and documentation of datasets
• Engagement and collaboration with researchers within the IEU and externally
• Assist with the organisation of meetings linked to the IEU

Essential

Experience in Epidemiology, standard statistical methods (e.g. regression models), performing analyses for genome-wide association studies (GWAS), using Linux/Unix operating systems, using R, Python or other common languages, and liaising with external collaborators

Desirable

Experience analysing exome or whole genome sequencing data, genotype calling and imputation of genotyping array data, additional ‘omics data (i.e. DNA methylation, transcriptomics, proteomics, metabolomics). Experience of using high-performance computing on a cluster, developing/sharing open-source code. Previous publications involving GWAS and analyses of exome or whole genome sequencing data.

Contract type: Open-ended with funding until 30/10/2026 initially

Work pattern: Full time/ 1 FTE

Grade: Grade J/ (Pathway 2)

Salary: £41,732 - £46,974 per annum depending on previous experience

School/Unit: Bristol Medical School

Shift pattern: 35 hours per week

This advert will close at 23:59 GMT on29/02/2024

For informal queries please contact: Dr Carolina Borges ([email protected] )

We recently launched our strategy  to 2030 tying together our mission, vision and values.

The University of Bristol aims to be a place where everyone feels able to be themselves and do their best in an inclusive working environment where all colleagues can thrive and reach their full potential. We want to attract, develop, and retain individuals with different experiences, backgrounds and perspectives – particularly people of colour, LGBT+ and disabled people - because diversity of people and ideas remains integral to our excellence as a global civic institution.