13473 - Research Fellow
| Dyddiad hysbysebu: | 04 Rhagfyr 2025 |
|---|---|
| Cyflog: | £41,064 i £48,822 bob blwyddyn |
| Oriau: | Llawn Amser |
| Dyddiad cau: | 03 Ionawr 2026 |
| Lleoliad: | Edinburgh, Scotland |
| Gweithio o bell: | Ar y safle yn unig |
| Cwmni: | University of Edinburgh |
| Math o swydd: | Cytundeb |
| Cyfeirnod swydd: | 13473 |
Crynodeb
Grade UE07: £41,064 to £48,822 per annum
CMVM / Centre for Clinical Brain Sciences
Full-time: 35 hours per week
Fixed-term: 4 years
The Opportunity:
We seek to hire a post-doctoral Research Fellow, with excellent statistical, organisational, and interpersonal skills, to apply advanced causal inference methods to analyse longitudinal data on the mediating pathways through which excess heat influences mental health for a Wellcome funded research study called ‘TOLAKARI’ (Transformation Of Lived experience And Knowledge of heat, Agriculture and depRession in India).
This post is full-time (35 hours per week). 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:
A PhD in Statistics, Data Science, or Epidemiology with experience in causal inference.
An MSC in statistics with expertise in causal inference would also be acceptable if the student is willing to complete a PhD.
Experience in causal inference techniques such as g-computation, and propensity score matching.
Other relevant analytical skills in advanced data wrangling and programming skills.
Good programming skills in Stata or R.
Proven ability to meet milestones according to project timelines.
CMVM / Centre for Clinical Brain Sciences
Full-time: 35 hours per week
Fixed-term: 4 years
The Opportunity:
We seek to hire a post-doctoral Research Fellow, with excellent statistical, organisational, and interpersonal skills, to apply advanced causal inference methods to analyse longitudinal data on the mediating pathways through which excess heat influences mental health for a Wellcome funded research study called ‘TOLAKARI’ (Transformation Of Lived experience And Knowledge of heat, Agriculture and depRession in India).
This post is full-time (35 hours per week). 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:
A PhD in Statistics, Data Science, or Epidemiology with experience in causal inference.
An MSC in statistics with expertise in causal inference would also be acceptable if the student is willing to complete a PhD.
Experience in causal inference techniques such as g-computation, and propensity score matching.
Other relevant analytical skills in advanced data wrangling and programming skills.
Good programming skills in Stata or R.
Proven ability to meet milestones according to project timelines.