Warning
This job advert has expired and applications have closed.
10520- Post Doctoral Research Fellow in Statistical Genetics
| Posting date: | 01 July 2024 |
|---|---|
| Salary: | £39,347 to £46,974 per year |
| Hours: | Full time |
| Closing date: | 15 July 2024 |
| Location: | Edinburgh, Scotland |
| Remote working: | On-site only |
| Company: | University of Edinburgh |
| Job type: | Temporary |
| Job reference: | 10520 |
Summary
UE07 £39,347-£46,974
CMVM- Human Genetics Unit/Institute of Genetics and Cancer
Full time 35 hours per week
Fixed Term until 31 March 2025
The Opportunity:
We are looking for a statistical geneticist with experience in large scale analyses of genomic data to work on a post funded by the National Institute for Health Research (NIHR) that aims are harness the use, integration and interpretation of large or high dimensional genetic and genomic datasets to investigate multi-morbidity. This post focuses on developing of mathematical models to analyse population-wide genetic and environmental factors linked to multimorbid clusters and to identify causal paths of disease progression and aggregation.
The successful candidate will lead a research programme to understand multi-morbidity in human populations. The successful candidate will interact with a large research community within the Artificial Intelligence community, genomics and health research (https://www.nihr.ac.uk/news/nihr-awards-12-million-to-artificial-intelligence-research-to-help-understand-multiple-long-term-conditions/28581, https://www.ed.ac.uk/usher/news-events/news-2021/artificial-intelligence-multimorbidity-nihr)
This post is full-time (35 hours per week), however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
Your skills and attributes for success:
-Technically proficient in statistical genetics methods (GWAS, LMM, etc)
-A track record in using or developing instrumental variable methods (e.g. Mendelian Randomization)
-Extremely good communication skills (written and verbal)
-Open and collegial
-Track record in high impact/high quality research publications
CMVM- Human Genetics Unit/Institute of Genetics and Cancer
Full time 35 hours per week
Fixed Term until 31 March 2025
The Opportunity:
We are looking for a statistical geneticist with experience in large scale analyses of genomic data to work on a post funded by the National Institute for Health Research (NIHR) that aims are harness the use, integration and interpretation of large or high dimensional genetic and genomic datasets to investigate multi-morbidity. This post focuses on developing of mathematical models to analyse population-wide genetic and environmental factors linked to multimorbid clusters and to identify causal paths of disease progression and aggregation.
The successful candidate will lead a research programme to understand multi-morbidity in human populations. The successful candidate will interact with a large research community within the Artificial Intelligence community, genomics and health research (https://www.nihr.ac.uk/news/nihr-awards-12-million-to-artificial-intelligence-research-to-help-understand-multiple-long-term-conditions/28581, https://www.ed.ac.uk/usher/news-events/news-2021/artificial-intelligence-multimorbidity-nihr)
This post is full-time (35 hours per week), however, we are open to considering part-time or flexible working patterns. We are also open to considering requests for hybrid working (on a non-contractual basis) that combines a mix of remote and regular on-campus working.
Your skills and attributes for success:
-Technically proficient in statistical genetics methods (GWAS, LMM, etc)
-A track record in using or developing instrumental variable methods (e.g. Mendelian Randomization)
-Extremely good communication skills (written and verbal)
-Open and collegial
-Track record in high impact/high quality research publications