Postdoctoral Research Fellow (Edinburgh)
UK DRI at Edinburgh University
Dementia is the biggest health challenge of our century.
To date there is no way to prevent it or even slow its progression, and there is an urgent need to fill the knowledge gap in our basic understanding of the diseases that cause it.
The UK Dementia Research Institute (UK DRI) is the biggest UK initiative driving forward research to fill this gap.
The Opportunity:
We are seeking a highly skilled and motivated Postdoctoral Researcher to join our Translational Cerebral Amyloid Angiopathy (CAA) Research Lab at the BHF-UK DRI Centre for Vascular Dementia Research. This role is ideal for someone with a strong technical and computational and background who is passionate about applying advanced data analysis to complex biological systems.
As a Postdoctoral Researcher, you will be performing in vivo optical microscopy experiments in rodent models. You will play a central role in developing and implementing computational approaches for the acquisition and analysis of high-resolution optical imaging data. Working with state-of-the-art in vivo two-photon microscopy datasets, you will design analysis pipelines, develop code, and extract meaningful insights from large, multidimensional imaging datasets. Your work will directly contribute to understanding the mechanisms underlying CAA and vascular dysfunction in neurodegenerative disease.
Alongside your computational focus, you will contribute to experimental workflows, including in vivo imaging studies and ex vivo tissue analysis, ensuring strong integration between data acquisition and analysis. This is a collaborative and interdisciplinary environment, where you will work closely with experimental researchers while leading on computational strategy and innovation.
Your skills and attributes for success:
We are looking for someone with strong programming skills (e.g. Python, MATLAB), experience in image processing and analysis, and the ability to handle complex datasets with precision and creativity. A proactive mindset, attention to detail, and enthusiasm for developing new computational methods are essential.