Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
applications* in close collaboration with other discipline experts (software, microelectronics and applications engineers). * except for RF payloads. ** including artificial intelligence and machine learning
-
at the interface between computational physics, machine learning and neuromorphic computing? Do you thrive for both fundamental and societal impact of your research? If so, we have a project for you
-
, ballistocardiography, and bio-radar) in combination with machine learning based algorithms for time series analysis into the whole OSA diagnosis and treatment pathway. During diagnosis unobtrusive sensors that can be
-
WGCNA is considered a plus); Proficiency in R; experience with Shiny app development is considered a plus; Proficiency in machine learning approaches; experience with NLP and AI is considered a plus
-
collaborate. We are also part of the MESA+ NanoLab , and have access to world-class cleanroom facilities. To learn more about the research within the Department of Biomechanical Engineering check our website
-
learning, allowing rapid but rigorous system architecture definition of a launch vehicle within the MBSE collaborative environment. You will also carry out research in the field of Uncertainty Quantification
-
backgrounds, cultures, and perspectives. Will you also contribute to making the world a little better? You have a part to play. If you want to learn more about working at Radboud University, follow our
-
with whom we collaborate. We are also part of the MESA+ NanoLab , and have access to world-class cleanroom facilities. To learn more about the research within the Department of Biomechanical Engineering
-
(Groningen), and the UK. This post-doc project offers a unique opportunity to work in an international environment and to acquire valuable research experience for someone who has recently completed a PhD in
-
records from satellite data, and/or improved methods of uncertainty characterisation, including the use of artificial intelligence and machine learning to improve or analyse satellite climate data records