14611 - Data analyst (medical imaging and statistics

CMVM / School of Neurological and Cardiovascular Sciences / Centre for Clinical Brain Sciences

Full-time: 35 hours per week

Fixed-term: 12 months (in the first instance)

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The University of Edinburgh is a world-class organisation. We look for the best in the field across all disciplines and provide a working environment where academics can develop their careers and passion for their chosen subject area. We offer the full range of academic roles and have a genuine focus on our students performance and wellbeing.

The Opportunity:

We are looking for an experienced data analyst with expertise in statistics, programming and data management to join our team conducting world-leading research into cerebral small vessel diseases. This role is suitable for someone with experience of analysing data from clinical datasets, in particular physiological (including sleep data), cognition, risk factors, neuroimaging, sociological measures and health registry-linked data in relevant disease cohorts (small vessel disease, stroke).

The post-holder will undertake a range of analyses of clinical studies of cerebral small vessel diseases, including brain MRI analysis and large longitudinal datasets. The successful candidate will be expected to manage and curate the data effectively, and publish scientific results in a timely fashion.

Your skills and attributes for success:

Expertise in statistical approaches and models, analytical techniques and methods

Experience of working with large clinical cohort studies including health registry-linked data

Understanding of medical image analysis methods and principles used in neuroimaging of vascular disease, ageing and neurodegeneration

Experience in medical research data management

A good track-record of publications in relevant fields.

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.