307 phd-studenship-in-computer-vision-and-machine-learning positions at DAAD in Germany
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
-
of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
-
Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
-
network of passionate young scientists in Munich. WHAT DO WE OFFER? A structured PhD program created by Munich-based Max Planck Institutes and Universities with English as the main language Individual
-
Description At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13
-
employees from over 50 nations, it is the largest institute of the Max Planck Society . The Research Group Computational Biomolecular Dynamics (Prof. Dr. Bert de Groot) is inviting applications for a PhD
-
Description The Graduate School Scholarship Program(GSSP) of the German Academic Exchange Service (DAAD) is offering two (2) doctoral scholarships to earn a PhD within the framework of “Ancient
-
committees • Comprehensive and structured PhD programme in the vibrant city of Cologne, Germany, conducted entirely in English • Individual career mentoring programme & coaching, a wide range of methodology
-
that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
-
play a central role in this interdisciplinary initiative. They will: Develop and apply machine learning (ML) methods – including surrogate modeling, feature extraction, and inverse design algorithms