Sort by
Refine Your Search
-
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
-
reactions. We welcome applicants from diverse backgrounds, including computational chemistry, bioinformatics, systems biology, and machine learning. The project offers a unique opportunity to collaborate
-
-learn, PyTorch) or physics-informed neural networks for thermal systems is a plus. Excellent communication and collaboration skills across disciplines. We offer DTU is a leading technical university
-
computer architecture. Responsibilities and qualifications You are expected to conduct independent research in collaboration with and under the guidance of experienced colleagues. Additionally, you will be
-
Job Description Are you a talented, self-motivated, and collaborative researcher who thrives in multidisciplinary environments? Are you excited by the idea of studying the carbon cycle in
-
for detecting subpicotesla magnetic fields? Can we control the trajectory of the current in magnetic fields? Can we form automated routines to answer the above questions? You will work in close collaboration with
-
activities Collaborate with researchers across Denmark and Europe in an interdisciplinary environment Help coordinate project efforts across En’Zync partners, including DTU, Aarhus University, the Danish
-
for innovative new projects (both local and international collaborations); Establish and maintain collaborations with partners within and outside DTU, as well as with private and public sector partners; Teach and
-
(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
-
-mortem and fractographic analysis Collaborating with colleagues at DTU Energy and industrial partners to improve the reliability of SOEC stacks Publishing your research results in relevant peer-reviewed