Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- Carnegie Mellon University
- ;
- The University of Chicago
- University of Cambridge
- Nature Careers
- Cornell University
- DAAD
- CNRS
- Radix Trading LLC
- Technical University of Munich
- The University of Iowa
- University of Bergen
- University of Oxford
- University of Pardubice
- Arizona State University
- Aston University
- Brookhaven Lab
- Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
- Delft University of Technology (TU Delft)
- Duke University
- Fondazione Bruno Kessler
- Forschungszentrum Jülich
- Fraunhofer-Gesellschaft
- Ghent University
- Institute of Computer Science of the Czech Academy of Sciences
- Instituto Politécnico de Setúbal
- KU Leuven
- Leibniz
- Luxembourg Institute of Socio-Economic Research (LISER)
- McGill University
- MedUni Vienna
- Sheffield Hallam University
- Tampere University
- Temple University
- The Ohio State University
- The University of Copenhagen
- Trinity College Dublin
- UNIVERSIDAD POLITECNICA DE MADRID
- University of Birmingham
- University of Bucharest
- University of Glasgow
- University of Liverpool
- University of Luxembourg
- University of Newcastle
- University of Oslo
- University of Sheffield
- University of Sydney
- University of Utah
- Vrije Universiteit Brussel
- Wageningen University & Research
- 40 more »
- « less
-
Field
-
integrating local flexibility markets through distributed AI-based coordination, market mechanism design, and cloud-to-edge computing. It aims to develop scalable machine learning methods for coordinating grid
-
field. Experience: At least three years of strong record of research productivity in machine learning and artificial intelligence. Expertise in AI/ML and interests in business and policy applications
-
language processing (NLP), large language models (LLMs), machine learning (ML), and data visualization. The candidate will leverage their expertise in AI, statistics, and programming to design, develop, and evaluate
-
Overview Nature offers a mechanism - called homeostasis - by which life forms can maintain their physical integrity and well being. On the other hand, a series of machines, including robots, cannot
-
validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
-
the successful applicant will develop novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic
-
manufacturing processes for processing using applied AI techniques. We anticipate the successful applicant will develop novel sensing approaches to combine with machine learning algorithms to solve real-world
-
methods of detection, identification, classification and tracking of objects of different sizes, shapes and speeds of movement using elements of artificial intelligence and machine learning. • Research work
-
under the “Cryptographic elements of trustworthy AI” project. The main research objectives for the project are the following: Analyze security of Machine Learning (ML) models against data modifications
-
the broader community. You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years of experience; OR PhD in