38 phd-position-data-mining Postdoctoral positions at University of London in United Kingdom
Sort by
Refine Your Search
-
interest to identify cancer drivers from genomic data using machine learning (Mourikis Nature Comms 2019, Nulsen Genome Medicine 2021), study their interplay the immune microenvironment (Misetic Genome
-
of Spiralian Asymmetric Cell Divisions”. This research position will reveal the mechanisms that drive the evolution of polar lobes during the first asymmetric cell divisions in animals with spiral cleavage. We
-
involves high level of collaboration with both the QMUL Space Plasma Group and the QMUL Detector Development Group. About You The successful candidate will have a PhD (or equivalent experience) in the field
-
have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
-
in the ongoing drive to reduce animal use in scientific research. Applicants must hold a PhD in Cell Biology or related discipline and have a track-record of success, as indicated by first-author
-
About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and
-
You The successful candidate will have a PhD (or soon to be awarded), or equivalent experience which has involved significant practical cell culture, and ideally experience with molecular biology
-
Institute (BCI) in London, with an ideal start date of July 2025. About You The successful candidate will be highly-motivated, have a PhD (or close to completion)* in a biological or computational discipline
-
dynamic strain and flow fields during flight. Candidates should hold a PhD in a relevant biology or engineering discipline and be competent with numerical simulations. Desirable competencies would include
-
treatments. To achieve this, we will develop personalised cardiac models at scale, and update these models over time, using imaging and electrical data collected by collaborators at multiple centres. We