Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Utrecht University
- University of Amsterdam (UvA)
- Leiden University
- Vrije Universiteit Amsterdam (VU)
- Wageningen University & Research
- Delft University of Technology (TU Delft)
- University of Twente
- AMOLF
- Eindhoven University of Technology (TU/e)
- Radboud University
- ;
- DIFFER
- European Space Agency
- Maastricht University (UM)
- NIOZ Royal Netherlands Institute for Sea Research
- Radboud University Medical Center (Radboudumc)
- Tilburg University
- 7 more »
- « less
-
Field
-
(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and
-
imaging datasets Ensure robust experimental design and reproducible research practices Publish in leading international journals and conferences Collaborate with interdisciplinary academic and clinical
-
industrial partners. Our group offers an open and collaborative environment in which we focus on hands-on learning and personal growth of all group members. We are looking for excited and talented candidates
-
for collaboration with experimental groups working on physical learning in electronics, mechanics, and living flow networks (Physarum Polycephalum). For more information about our work, see: [1] Stern, Hexner, Rocks
-
at the intersection of reinforcement learning and stochastic optimization developing novel methodologies that advance both theoretical insights and practical applications collaborating across disciplines and contribute
-
intensively collaborate with the two PhD candidates already appointed within the project. This is what you are going to do As the Postdoctoral researcher for Work Package 3, you will be appointed
-
full projects, followed by the analysis, interpretation and reporting of data and results. You will pro-actively promote proteomics services and acquire new collaborative projects. The projects will vary
-
. Applicants focused on topic 2 should be able to deal with logistical issues and challenging conditions for field campaigns in Alaska and Canada. Selected candidates will closely collaborate with other team
-
track record in one or more of the following fields: (1) human-computer interaction, collaborative AI, (2) Generative AI/machine learning, (3) interaction design, experimental design, or evaluation
-
)science, be supervised by Dr. Nicholas Judd, and be embedded within Professor Kievit’s lab. They will work with international collaborators to capitalize on the recent rapid increase in the availability