Sort by
Refine Your Search
-
Listed
-
Employer
- University of Oxford
- KINGS COLLEGE LONDON
- DURHAM UNIVERSITY
- Durham University
- University of Cambridge
- University of Oxford;
- ;
- King's College London
- Heriot Watt University
- UNIVERSITY OF VIENNA
- AALTO UNIVERSITY
- Nature Careers
- The University of Edinburgh;
- University of Cambridge;
- University of Liverpool
- ; University of Copenhagen
- Aston University
- City University London
- Heriot-Watt University;
- Imperial College London
- John Innes Centre
- Medical Research Council
- Swansea University
- University of Glasgow
- University of Leeds
- University of Liverpool;
- University of West London
- University of York;
- 18 more »
- « less
-
Field
-
scientific publications, patents, and seeing collaborators translate our work into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and
-
into real-world settings. You will be responsible for developing machine learning and AI algorithms for a range of data and applications (e.g. natural language processing, multivariate time-series data
-
, delivering tested methods, and creating algorithms to expand MMFM capabilities across domains like cardiology, geo-intelligence, and language communication. The postholder will help lead a project work package
-
that surround the developing embryo in plants. We are mainly working with the model liverwort Marchantia polymorpha, for which we have developed extensive genetic tools, but will extend this to several other
-
and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
-
computational frameworks that combine 4D point cloud data, geospatial analysis, and advanced ML/DL algorithms. Integrate dynamic environmental datasets into immersive and interactive prototypes for scenario
-
Role Description Department We are seeking an experienced mathematical modeller. Our group is developing a range of advanced genetics-based methods for controlling mosquito-borne diseases, based
-
project aims to address the current limitations of traditional frame-based sensors and associated processing pipelines with a new family of algorithmic architectures that mimic more closely the behaviours
-
to numerical simulation algorithms? Then apply now to join our team of theoretical researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere of play: As a
-
work closely with lab members but with a focus on EV-associated fungal proteins. They will assist in protocol and technique development and use reverse genetics for functional analysis of EV candidates