Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
Computer Science or related fields • Strong background in machine learning • Strong programming skills in Python and experience with deep learning frameworks (PyTorch or similar) • Proficient in spoken and written
-
30.04.2025, Wissenschaftliches Personal The Leibniz Institute for Food Systems Biology at the Technical University of Munich (Leibniz- LSB@TUM) is a research institution of the Leibniz Association
-
qualitative methods; some background in or willingness to learn computational social science methods as well as R and/or Python is highly desirable. Willingness to develop an ambitious empirical research
-
15.04.2025, Wissenschaftliches Personal The Lab for Artificial Intelligence in Medical Imaging (www.ai-med.de) is inviting applications for a fully funded PhD position in interpretable machine learning for dementia prediction. see here:...
-
School of Engineering and Design and maintain strong links with the computer science community. One of our key research areas is the design and operation of intelligent networked production systems
-
(or equivalent) with excellent academic results in Aerospace Engineering, Mechanical Engineering, Electrical/Computer Engineering, Physics, or a related field at the time of appointment Required knowledge
-
Engineering, Mechanical Engineering, Electrical/Computer Engineering, Physics, or a related field at the time of appointment Required knowledge: Excellent knowledge of spaceflight mechanics or engineering
-
26.02.2025, Wissenschaftliches Personal We are looking for a postdoctoral researcher (f/m/d) with a PhD in Simulation Technology, Computer Science, Mechanical Engineering, or a related field. About
-
Academic staff for the "Learning Sciences and Educational Design Technologies" working group (f/m/d)
19.03.2025, Wissenschaftliches Personal About us The working group Learning Sciences and Educational Design Technologies is looking for a post-doctoral re-searcher (m/f/d), TV-L E 13, 75%, initially
-
must also be reduced. To analyze and control thermoacoustic instabilities, we combine fluid mechanics, acoustics, and combustion with methods from control engineering, nonlinear dynamics, and data-driven