201 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" Postdoctoral positions in Denmark
Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
employ cutting-edge single-cell and spatial omics technologies with bioinformatics and machine learning to decipher principles of gene regulation underlying cell identity and its disruption in human
-
Boson Sampling machine. These ambitious projects all focus on addressing fundamental and technical challenges in photonic quantum computing using continuous-variable entanglement. The successful candidate
-
work on development of wave energy and offshore wind. Most of our research is focused around work in our wave flume and basin. Further description of the group may be found here: https://vbn.aau.dk/en
-
Applications are invited for a postdoctoral position in the group of Dr Aleksandr Gavrin ( https://mbg.au.dk/a-gavrin/ ) at the Department of Molecular Biology and Genetics, Aarhus University
-
fishing activities, major shipping routes, and offshore development locations. The EU Oceans Pact highlight the need to assess and manage dumped munitions. Two EU-funded projects, MUNI-RISK ( https://muni
-
and postdoc cohort positions at http://www.capex-p2x.com . The research area will be within design and modeling of pulsed power supplies utilizing power electronics technology for plasma generation
-
in Computer Science, Machine Learning, Artificial Intelligence, Computational Biology, or a closely related field Has strong theoretical and practical experience in deep learning Has hands
-
the Machine Learning and Artificial Intelligence. Solid mathematical and analytical skills. Knowledge about statistical machine learning, robotic perception, multimodal AI algorithms. Experience in programming
-
, semiparametric inference), and ideally experience with high-dimensional econometrics, machine learning, or advanced causal inference methods. Demonstrate the ability and motivation to pursue independent research
-
and maintenance of monitoring buoys and related sensor systems. Apply image analysis and machine learning techniques to ecological datasets. Develop and implement multi-platform monitoring frameworks