Sort by
Refine Your Search
-
Listed
-
Employer
- Technical University of Denmark
- Nature Careers
- University of Southern Denmark
- Aarhus University
- University of Copenhagen
- Aalborg University
- ; Technical University of Denmark
- ; University of Copenhagen
- ;
- ; University of Southern Denmark
- Copenhagen Business School , CBS
- European Magnetism Association EMA
- 2 more »
- « less
-
Field
-
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
-
Embedded AI, Edge AI, TinyML, and AIoT, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system
-
and proposal preparation. Required qualifications: As a formal qualification, you must hold a PhD degree (or equivalent) in computer science, computer engineering, networking, or related fields relevant
-
forecasting. You will get the opportunity to participate and influence the development of advanced forecast solutions combining weather forecasts and novel machine learning/statistical forecasting methods
-
developed algorithms with the designed hardware in the best way. Document design specifications, and design trade-offs clearly. Qualifications Applicants should hold a PhD in electronics, computer engineering
-
. Postdocs will be supported in improving their CVs for academic careers. This includes co-supervision of MSc and PhD students, teaching opportunities, and proposal development. You can learn more about ESE
-
Electrophysiological signal processing of, e.g., EEG, ECG, EMG, etc. Health data science, incl. modern machine, and deep learning methods, Cloud-based platforms like MS Azure or Google Colab Health data standards, like
-
analysis Close collaboration with an interdisciplinary team. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise MSc and PhD student
-
spatio-temporal regularization, discrete tomography, low-dimensional latent representations and machine learning. The ultimate aim is to reduce the carbon footprint for the construction industry and enable
-
. theses at the interface between structural engineering and machine learning. You will disseminate your research through peer-review publications and participation in international conferences. You will