Sort by
Refine Your Search
-
Listed
-
Employer
- Technical University of Denmark
- Nature Careers
- Aarhus University
- University of Southern Denmark
- University of Copenhagen
- Aalborg University
- ;
- Copenhagen Business School , CBS
- Aalborg Universitet
- Copenhagen Business School
- European Magnetism Association EMA
- Technical University Of Denmark
- University of Oxford
- 3 more »
- « less
-
Field
-
The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
-
The Department of Agroecology at Aarhus University, Denmark, is offering a postdoctoral position in machine learning for advanced peatland mapping, starting 01-12-2025 or as soon as possible
-
At the Technical Faculty of IT and Design, Department of Sustainability and Planning a position as Postdoc in Generative AI for Student Learning is open for appointment from 01. October 2025 or soon
-
qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, or electrical engineering. Hardware design in a hardware description language such as Chisel, VDHL, or Verilog
-
expected to teach relevant courses at the bachelor’s and master’s levels with supervision from colleagues. Lastly, you will be advising students at all levels, including Master and PhD students
-
, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus
-
, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit
-
(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
-
. The research will bridge both established and emerging technical expertise within the section, encompassing areas such as FPGA and neuromorphic computing, Edge AI, machine learning, power electronics, and self