We are seeking a postdoctoral researcher with expertise in bioinformatics/applied health data science and experience in molecular/genetic epidemiology and/or biomedical research. The successful candidate will join the Data Mining Epidemiological Relationships Research Programme in the vibrant multi-disciplinary research environment of the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol. This post is funded for 4 years and would suit someone aiming to build their expertise in population health data science or develop ideas for a future fellowship application.
The successful applicant will have access to a range of training and career development opportunities, including a range of population health short courses (http://www.bristol.ac.uk/medical-school/study/short-courses/ ) and training in research computing (http://www.bristol.ac.uk/acrc/acrc-training/ ). We collaborate with leading academic and industry groups in the UK and around the world, providing the successful applicant with opportunities to build their professional network.
You will work on the development and application of new approaches to identification and prioritization of drug targets using Mendelian randomization (MR), genetic colocalization, rare genetic variants, molecular pathway and drug perturbation data. You will integrate data from many data sources, including major biobanks, public bioinformatic databases and you will also work with the OpenGWAS database (gwas.mrcieu.ac.uk ) and EpiGraphDB (www.epigraphdb.org ) knowledge graph developed within the IEU. You will be expected to write papers based on your research and will be encouraged to develop new open source analytical packages in R or Python. You will work in collaboration with other members of the team and a wider network of collaborators, and be encouraged to develop your own research ideas and projects related to the core themes of the programme. You will be encouraged to get involved in postgraduate research supervision.
The successful applicant will have a strong biological/biomedical background with experience of coding and data analysis, and will be qualified to PhD level (or equivalent). Strong programming skills (in R or Python), machine learning experience, and an ability to work effectively in a multi-disciplinary environment would be an advantage.
Contract type: Open-ended with fixed funding until 31/03/2028
Work pattern: Full time/1 FTE
Grade: Grade J/Pathway 2
Salary: 41,732 - 46,974 per annum
School/Unit: Bristol Medical School
Shift pattern: 35 hours per week
This advert will close at 23:59 GMT on 04/02/2024
For informal queries please contact: Prof Tom Gaunt ([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.
Available documents
We are seeking a postdoctoral researcher with expertise in bioinformatics/applied health data science and experience in molecular/genetic epidemiology and/or biomedical research. The successful candidate will join the Data Mining Epidemiological Relationships Research Programme in the vibrant multi-disciplinary research environment of the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol. This post is funded for 4 years and would suit someone aiming to build their expertise in population health data science or develop ideas for a future fellowship application.
The successful applicant will have access to a range of training and career development opportunities, including a range of population health short courses (http://www.bristol.ac.uk/medical-school/study/short-courses/ ) and training in research computing (http://www.bristol.ac.uk/acrc/acrc-training/ ). We collaborate with leading academic and industry groups in the UK and around the world, providing the successful applicant with opportunities to build their professional network.
You will work on the development and application of new approaches to identification and prioritization of drug targets using Mendelian randomization (MR), genetic colocalization, rare genetic variants, molecular pathway and drug perturbation data. You will integrate data from many data sources, including major biobanks, public bioinformatic databases and you will also work with the OpenGWAS database (gwas.mrcieu.ac.uk ) and EpiGraphDB (www.epigraphdb.org ) knowledge graph developed within the IEU. You will be expected to write papers based on your research and will be encouraged to develop new open source analytical packages in R or Python. You will work in collaboration with other members of the team and a wider network of collaborators, and be encouraged to develop your own research ideas and projects related to the core themes of the programme. You will be encouraged to get involved in postgraduate research supervision.
The successful applicant will have a strong biological/biomedical background with experience of coding and data analysis, and will be qualified to PhD level (or equivalent). Strong programming skills (in R or Python), machine learning experience, and an ability to work effectively in a multi-disciplinary environment would be an advantage.
Contract type: Open-ended with fixed funding until 31/03/2028
Work pattern: Full time/1 FTE
Grade: Grade J/Pathway 2
Salary: 41,732 - 46,974 per annum
School/Unit: Bristol Medical School
Shift pattern: 35 hours per week
This advert will close at 23:59 GMT on 04/02/2024
For informal queries please contact: Prof Tom Gaunt ([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.
Available documents
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