Sort by
Refine Your Search
-
Category
-
Program
-
Employer
-
Field
-
Are you ready to develop and implement the latest Reinforcement Learning approaches? At the Fraunhofer Application Center for "Connected Mobility and Infrastructure" in Ingolstadt, a unique
-
their final (Master’s) thesis with a focus on machine learning / reinforcement learning. Our research at the Fraunhofer Application Center “Connected Mobility and Infrastructure” in Ingolstadt addresses current
-
their final (Master’s) thesis with a focus on machine learning / reinforcement learning. Our research at the Fraunhofer Application Center “Connected Mobility and Infrastructure” in Ingolstadt addresses current
-
Learning Algorithm for Grid Optimization linked to Bayesian uncertainty outputs Test bidirectional interaction: Bayesian updates → Reinforcement Learning policy adaptation → grid performance feedback
-
team in the fields of artificial intelligence and simulation, urban air mobility – autonomous flying and autopilot, autonomous mobility or traffic optimization using reinforcement learning. What you
-
tasks Basic and/or applied research in artificial intelligence and deep machine/reinforcement learning for optimizing quantum computing algorithms andcsimulation of quantum materials Development
-
., interventions), advanced statistical modeling skills (e.g., Bayesian mixed models), advanced cognitive modeling skills (e.g., signal detection theory, evidence accumulation models, reinforcement learning), and
-
Postdoc (f/m/d) in Machine Learning for Quantum Computing and Simulation of Quantum Matter / Comp...
networks, deep learning (particularly deep reinforcement learning), quantum physics, quantum chemistry, quantum computing/algorithms, high-performance computing, and Monte Carlo methods # Experience with ML
-
, survey) or applied microeconometrics, and applied economics. You have experience with big data and machine learning methods? This would be a particular asset! With excellent English language skills, both
-
) for infrastructure systems subject to geotechnical failure mechanisms. While advances in AI methods for reinforcement learning have been exploited for PM planning and lead to significant improvements over traditional