Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- KINGS COLLEGE LONDON
- University of Oxford;
- AALTO UNIVERSITY
- King's College London
- UNIVERSITY OF VIENNA
- Durham University
- University of Liverpool
- University of Liverpool;
- ;
- City University London
- Heriot Watt University
- Lancaster University
- Nature Careers
- Northumbria University;
- University of Cambridge;
- University of Leicester
- University of Leicester;
- University of London
- University of Sheffield
- 10 more »
- « less
-
Field
-
hold, or be close to completion of, a relevant PhD/DPhil in one of the following subjects: computational genomics, genetic or molecular epidemiology, medical statistics or statistical genetics. You must
-
to reconstruct subsurface defects; Implement image/signal‑processing or machine‑learning pipelines for automated flaw characterisation; Collaborate with the Federal University of Rio de Janeiro, including short
-
or a closely related field (PhD candidates who have submitted or are about to submit their thesis will be considered) Experience of machine learning frameworks (e.g. TensorFlow) Knowledge of Python and C
-
skills. Aware of the ethical issues around working with Big Data. Desirable criteria Experience applying advanced statistical or machine learning methods to complex datasets. Evidence of involvement in
-
statistical or machine learning methods to complex datasets. Evidence of involvement in grant writing or development of independent research ideas. A commitment to teaching the next generation of researchers
-
statistical or machine learning methods to complex datasets. Evidence of involvement in grant writing or development of independent research ideas. A commitment to teaching the next generation of researchers
-
skills (e.g. Python, Julia) to merge concepts of chemical engineering, operations research and computer science, as you may also need to deploy machine learning to support data analytics and complex
-
hold, or are close to completing, a PhD in robotics, robot learning, or a closely related field. You possess strong expertise in deep learning and robot navigation, with hands-on experience in deploying
-
they are kept fully up to date with progress and difficulties in the research projects. It is essential that you hold a PhD/DPhil in a quantitative discipline (e.g. Statistics, Machine Learning, Biostatistics, AI
-
of atomistic modelling of ferroelectric materials 2. Experience in development and application of machine learned potentials * Please note that this is a PhD level role but candidates who have submitted