Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
the Division for Computer network and systems and the employment is placed with Chalmers University of Technology. Our research spans from theoretical computer science to applied systems development. We provide
-
and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
-
application! Your work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning
-
consist of the following: Mathematical analysis of ecological and eco-evolutionary models, involving pencil-and-paper calculations; Computer simulations of more complex models which do not easily lend
-
totaling 60 ECTS credits) and join an international research team with backgrounds in sociology, political science, network science, statistics, and machine learning. More information on the PhD program can
-
of robotics, electromobility and autonomous driving. We offer advanced PhD courses where we extend the fundamentals in optimal control, machine learning, probability theory and similar. The research and
-
/thesis: Challenges and opportunities with remote sensing and machine learning in forestry Research subject : Soil science Description: WIFORCE Research School Do you want to contribute to the future
-
. The position is placed in the Division for Computer Networks and Systems and is formally employed by Chalmers University of Technology. Our research spans from theoretical computer science to applied systems
-
livable cities. The project will be based in the AI Laboratory for Molecular Engineering (AIME) , led by Assistant Professor Rocío Mercado Oropeza, where researchers develop new machine learning (ML
-
. The project will be based in the AI Laboratory for Molecular Engineering (AIME) , led by Assistant Professor Rocío Mercado Oropeza, where researchers develop new machine learning (ML) methods to tackle