Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Birmingham
- ;
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- UNIVERSITY OF SOUTHAMPTON
- Nature Careers
- University of Nottingham
- Aston University
- The University of Southampton
- University of Bristol
- City University London
- Manchester Metropolitan University
- University of Oxford
- University of Surrey
- Birmingham City University
- CZECH UNIVERSITY OF LIFE SCIENCES
- QUEENS UNIVERSITY BELFAST
- Swansea University
- UNIVERSITY OF SURREY
- University of Glasgow
- University of Sheffield
- University of Stirling
- 11 more »
- « less
-
Field
-
and refine algorithms and models for large-scale language processing tasks, with a focus on healthcare data Contribute to developing new models, techniques and methods for clinical machine learning
-
HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
-
algorithms might support the wider integration of, and uptake of, renewable energy technologies for particular use cases and considering a variety of perspectives (technical/policy/social/economic). You will
-
conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
-
include but are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources
-
, the appointed candidate will work closely with the line manager to develop novel control algorithms in EAP soft robotics combining Gaussian Predictors, hands-on laboratory experiments and JULIA computing
-
the prevalence and risk of modern slavery. There will be a focus on Bayesian nonparametric methods and practical development of MCMC algorithms that can be applied to data. Translating the project findings
-
development of mathematical models and algorithms for the analysis of biopharmaceutical manufacturing processes with a focus on assuring safety and alignment of machine learning models with the expected
-
Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing techniques to enable large-scale data search
-
conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences