Sort by
Refine Your Search
-
Employer
- University of Oxford
- King's College London
- University of Oxford;
- University of Liverpool
- Durham University
- University of London
- Queen Mary University of London;
- University of Cambridge;
- Bournemouth University;
- HITS gGmbH
- Lancaster University
- Liverpool School of Tropical Medicine;
- UCL
- University of Cambridge
- University of Manchester
- University of Reading;
- University of West London
- University of York
- 8 more »
- « less
-
Field
-
: Molecular modelling and simulation experience during PhD Ability to present complex information effectively to a range of audiences Experience of manipulating and visualizing large datasets We value
-
out research for a discrete area of a large project. The post holder provides guidance to less experienced members of the research group, including postdocs, research assistants, technicians, and PhD
-
, Rubin-LSST, PFS, JCMT, Litebird as well as participation at co-I level of instruments on large explorer mission concepts such as Cassini and JUICE with participation in many other mission and instrument
-
outcome sets. You will either need a PhD (or be nearing completion), in computer science, data science, artificial intelligence/machine learning (AI/ML), health data science, bioinformatics or a related
-
B cell lymphomas including diffuse large B cell lymphoma and Burkitt lymphoma. They arise as a byproduct of somatic hypermutation, when the enzyme activation-induced deaminase (AID) generates DNA
-
. The role includes implementing developed techniques and algorithms in high-quality software that adheres to group standards and evaluating them on large-scale benchmarks. You will take an active role in
-
protocols, and test hypotheses and analyse scientific data. You will be expected to contribute ideas for new research projects, develop ideas for generating research income, present detailed research
-
successful in this role, you will hold (or be close to completing) a PhD/DPhil in machine learning, artificial intelligence, computer science, epidemiology, health data science, or a related quantitative
-
of research investigating cancer risk and prevention. The appointee will work closely with Professor Ruth Travis, Dr Karl Smith-Byrne and other members of the research team, using large-scale epidemiological
-
and spatial analysis techniques to large-scale spatial transcriptomics and imaging datasets, using tools such as MuSpAn to identify spatial biomarkers and uncover the biological mechanisms driving