Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
for expertise in AI-driven fetal brain imaging, clinical obstetrics, pregnancy physiology, and global health technology innovation, particularly aimed at low- and middle-income countries (LMICs). The primary
-
/ computational biology / life sciences discipline, or relevant field such as computer science, mathematics or statistics. You will have substantial experience in the analysis of large datasets, which will allow
-
with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute
-
-time for 12 months About us: At the Department of Physiology Anatomy & Genetics (DPAG) we undertake discovery science where we reassemble physiological processes at the molecular, cellular, tissue and
-
About the role We are looking for a highly motivated and curious research assistant with a background in biology, neuroscience or a related field to join the exciting “innovaTEbehaviour” project
-
preparation, imaging modalities and settings, data processing, as well as image analysis and data presentation. You will lead in the development of bespoke analysis pipelines and train users in the independent
-
, immunofluorescence, cellular biochemistry, proteomics, and image-based analysis. There’s also scope to expand into computational biology, high-content imaging analysis, and data-driven modeling, depending on your
-
of the Institute is to improve tools in, and knowledge from, genetics, genomics, molecular and single cell biology, spatial imaging, machine learning and novel methods of data handling to study the pattern
-
• Ability to adapt to emerging technologies in biophysics and computational methods • Knowledge of concepts in digital image processing and analysis • Knowledge of ImageJ or willingness to learn it
-
collaboration with the Translational Gastroenterology Unit (TGU) and the Ludwig Institute of Cancer Research (LICR) we aim to develop a computer guided endoscopy image recognition system that will support