Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
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
-
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
-
patent filings. The work will be centred around topics such as machine learning for communications, communication theory, signal processing for communications, coding theory, and information theory. Your
-
, 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
-
are part of a sub-project on Algorithmic Sustainability in association with Professor Christina Lioma and her Machine Learning research team in the Department of Computer Science at the University
-
, 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
-
motivated researcher with: Strong background in control and optimization, preferably with experience in model predictive control (MPC). Solid skills in machine learning algorithms and data analysis
-
(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
-
Post Doctoral Researcher in Digital Twins CO2-to-Protein production in collaboration between the ...
collaboration between the Department of Electrical and Computer Engineering and the Novo Nordisk Foundation CO2 research center, Aarhus University, we aim to address this opportunity by developing digital twins