Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- ;
- Heriot Watt University
- KINGS COLLEGE LONDON
- Durham University
- UNIVERSITY OF VIENNA
- University of Cambridge
- Nature Careers
- University of London
- King's College London
- University of Glasgow
- University of Liverpool
- ; Technical University of Denmark
- ; University of Reading
- AALTO UNIVERSITY
- City University London
- Nottingham Trent University
- Plymouth University
- University of Newcastle
- University of Reading
- 10 more »
- « less
-
Field
-
. The Associate will develop machine learning algorithms for detecting events of interest and their classification thus to avoid emergencies, prioritize repair and maintenance and plan better for the future
-
://www.kcl.ac.uk/research/pavri-group About the role The project is focused on combining artificial intelligence (AI)-based machine learning and experimental validation to decipher the mechanism of somatic
-
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
-
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
-
laminar fMRI studies of prefrontal, auditory, and hippocampal circuits in awake, behaving nonhuman primates. You will hold a PhD in neurobiology, neuroscience, or a related field, with a strong publication
-
PhD in Chemistry or a relevant subject area, (or be close to completion) prior to taking up the appointment. The research requires experience in computational chemistry, including machine learning
-
evaluations, attacks on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related
-
, Synthetic Data for Machine Learning in Privacy Research, Formalization of Security Risk Management, and Security and Privacy of Blockchain Technologies. In the long term, we are concerned with understanding
-
learning methods to improve the understanding, treatment and prevention of human disease. The successful candidate will develop novel statistical and machine learning algorithms to address key challenges in
-
a PhD/DPhil or equivalent in a quantitative discipline such as computer science, statistics, machine learning, statistical or population genetics, or a related field. They should have experience in