Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oxford
- KINGS COLLEGE LONDON
- AALTO UNIVERSITY
- University of Oxford;
- King's College London
- UNIVERSITY OF VIENNA
- ;
- University of Liverpool
- City University London
- Durham University
- Heriot Watt University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Cambridge;
- University of Liverpool;
- Aston University
- Bournemouth University;
- College of Chemistry and Molecular Engineering, Peking University
- Imperial College London
- King's College London;
- Medical Research Council
- Nature Careers
- Northumbria University;
- Technical University of Denmark
- The University of Edinburgh;
- University of Bath
- University of Cambridge
- University of Leeds
- University of London
- University of Nottingham
- University of Sheffield
- 20 more »
- « less
-
Field
-
Machine Learning, Statistics, Computer Science or closely related discipline. They will demonstrate an ability to publish, including the ability to produce high-quality academic writing. They will have the
-
About the Role We are seeking an enthusiastic and motivated postdoctoral researcher to apply advanced data analytics and machine learning techniques to real-world clinical data in the field of viral
-
Aalto University is looking for an Postdoctoral Researcher in Artificial Intelligence / Machine Learning Engineering [Academic Research Software Engineer] to a postdoctoral-level position. The
-
and decision-making in humans and machine learning systems. The post-holder will have responsibility for carrying out rigorous and impactful research into human-AI interaction and alignment, with a
-
Vision or Machine Learning. You should have a strong publication record at the principal international computer vision and machine learning conferences and should hold sufficient theoretical and practical
-
will work as a member of an interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine
-
will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
-
interdisciplinary team (including experts in machine-learning and microbiology) to establish microfluidics-enabled microscopy assays on single bacterial cells to determine their antibiotic resistance. Your work will
-
collaborative links thorough our collaborative network. The researcher should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely related field. You have an
-
innovative EU-funded project at the intersection of polymer chemistry, computational modelling, and machine learning. The primary role is to develop a complete in silico framework to accelerate the discovery