Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- Nature Careers
- UNIVERSITY OF SOUTHAMPTON
- University of Nottingham
- University of Birmingham
- Imperial College London
- KINGS COLLEGE LONDON
- UCL;
- University of Leeds;
- ;
- King's College London
- Plymouth University
- UNIVERSITY OF SURREY
- University of Bath;
- University of Oxford
- Aston University
- Aston University;
- City University London
- Queen's University Belfast
- Queen's University Belfast;
- The University of Southampton
- University of Exeter
- University of Plymouth;
- University of Southampton;
- ; University of Oxford
- Cranfield University
- Cranfield University;
- EMBL-EBI - European Bioinformatics Institute
- Imperial College London;
- Lancaster University
- Lancaster University;
- NORTHUMBRIA UNIVERSITY
- Northumbria University;
- Nottingham Trent University
- QUEENS UNIVERSITY BELFAST
- Technical University of Denmark
- The University of Edinburgh;
- UNIVERSITY OF MELBOURNE
- University College London
- University of Bath
- University of Brighton
- University of Bristol
- University of Bristol;
- University of Glasgow
- University of Hertfordshire;
- University of Leeds
- University of London
- University of Manchester
- University of Nottingham;
- University of Stirling
- University of Stirling;
- 41 more »
- « less
-
Field
-
, output validation and reporting. Developing integrative strategies for a diverse set of data, integrating the outcomes to inform future projected trend analysis. Applying statistical and machine learning
-
with Circular Economy principles, machine learning, artificial intelligence, and SQL databases. A relevant degree in Engineering, computer science and data analytics or a closely related subject and a
-
-house experiment results Use state-of-the-art machine learning models to develop a multi-scale droplets evaporation model Assists in co-supervision of Final Year Projects (FYP) or capstone projects
-
Partnership between UCL and AstraZeneca and to work as part of a cross-disciplinary team across both sites (London and Cambridge). This post is focused on the use of machine learning models of protein
-
research experience to include: Experience developing novel deep learning methodologies (e.g. transformer models, Convolutional Neural Networks, Auto-encoder models, or LSTM networks). Demonstrable ability
-
trend analysis. Applying statistical and machine learning to project future data analysis. Managing and analysing large data sets using efficient data structures and providing infrastructure for sharing
-
large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
-
researcher to help us deliver it. By combining coherent Raman scattering with machine-learning models trained on plant mutants, the project will shed new light on the cellular-level biochemistry that governs
-
Electronic Engineering, Control Engineering, Computer Science or a very closely related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm
-
therapeutic discovery and providing commercial growers sustainable methods to meet increasing global food demand. Responsibilities Apply machine learning techniques, statistical modelling, and chemometric