10 big-data-and-machine-learning-phd Postdoctoral positions at Technical University of Denmark in Denmark
Sort by
Refine Your Search
-
, glacier speedup, and ice-ocean interaction. Candidates will work with satellite altimetry, velocity datasets, and climate data to quantify ice sheet mass balance and dynamics. Applicants should hold a PhD
-
intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and
-
predictive framework linking genomic data to extinction risk, working at the interface of evolutionary genomics, simulation modelling, and machine learning. By integrating forward-in-time simulations, real
-
meetings Potentially participate in Arctic field campaigns Be working with large data sets and developing algorithms. You should be highly motivated, self-driven, and possess strong work ethics, team spirit
-
systems Strong skills in data-driven analysis and modelling, simulation, control, and validation Familiar with modeling of PtX and storage technologies, model predictive control, machine learning
-
(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
-
, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
-
simulations using, e.g., COMSOL, Lumerical, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research
-
interest and documented skills and experience in using computer-based tools to analyse, simulate and predict capture performance of active and passive fishing gears. A track record of publishing in peer
-
qualification, you must hold a PhD degree (or equivalent). The successful candidate must moreover exhibit the following professional and personal qualifications: Strong background within machine learning learning