Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- University of Oxford
- University of Oxford;
- University College Cork
- AALTO UNIVERSITY
- Durham University
- Queen Mary University of London;
- UNIVERSITY OF VIENNA
- KINGS COLLEGE LONDON
- King's College London
- MAYNOOTH UNIVERSITY
- Nature Careers
- University of Bath
- University of Liverpool
- University of Liverpool;
- University of London
- ;
- Aston University
- Cardiff University
- Imperial College London
- King's College London;
- MUNSTER TECHNOLOGICAL UNIVERSITY
- Plymouth University
- RCSI - Royal College of Surgeons in Ireland
- University of Cambridge;
- University of Canterbury, New Zealand;
- University of Glasgow;
- University of Lincoln
- University of Lincoln;
- 18 more »
- « less
-
Field
-
that integrate multi-omics data to uncover mechanisms of disease, cellular resilience, and therapeutic response. The post holder will lead research applying large-scale machine learning and foundation models
-
schools, doctoral supervision, and software outputs central to the Centre’s mission. About You You will have, or be close to completion of, a PhD/DPhil in Statistics, Machine Learning, Data Science, or a
-
modelling, and machine learning approaches to analyse large-scale datasets, including bulk and single-cell sequencing, gene expression arrays, proteomics, and metabolomics. Working closely with senior
-
and data processing skills: experience of programming in one or more languages (e.g. R, C/C++, Python, Matlab). Practical experience of algorithm development and implementation of machine learning
-
, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial
-
and machine learning models. To be successful in this role, you will have excellent communication skills and written English, strong quantitative and analytical skills, the ability to work creatively
-
fundamental research, we create widely used open-source software including autodE, cgbind/C3, and mlp-train. Our recent advances in Machine Learning Interatomic Potentials (MLIPs) form the foundation of our ERC
-
, machine learning, or data analytics. As a proficient programmer (ideally Python), you will be curiosity-led, with exceptional communication skills, and thrive in a highly interdisciplinary environment. You
-
operational practices • Systematically exploring different formulations of mixed-integer constraints in grid optimisation problems • Developing machine learning models to accelerate mixed-integer
-
their surfaces. Machine learning methods are used to close the complexity gap. Currently, the group consists of three full professors, one associate professor, 6 postdocs and about 15 PhD and 7 master