35 machine-learning scholarships at Chalmers University of Technology

PhD student in AI / Machine Learning - Reinforcement Learning

This PhD position offers a unique opportunity to dive into the exciting area of reinforcement learning within the broader landscape of AI and machine learning. As a candidate, you'll have the chance

PhD Student in Machine Learning for Information/Communication Technology

high-speed data traffic over very long distances, and they collectively constitute the so-called Internet backbone. By harnessing recent advances in machine learning and artificial intelligence (AI

PhD student in Neuro-symbolic AI for Mathematical Discovery

researchers working in AI across Sweden and abroad. Major responsibilities We are looking for a PhD student with an interest in neuro-symbolic AI (machine learning and symbolic methods) to work as a researcher

PhD student in Neuro-symbolic AI for Mathematical Discovery

PhD student with an interest in neuro-symbolic AI (machine learning and symbolic methods) to work as a researcher on this project, which will include both implementation work and experimentation. It is

PhD position in bioinformatics and artificial intelligence

computing and programming skills (e.g. Python and R), experience in the Linux/UNIX computer environment, and, preferably, previous experience in working with machine learning and/or artificial intelligence

PhD student position in Safety Engineering for Trustworthy Autonomy

fields such as software engineering (e.g., ICSE, FSE), formal methods (e.g., CAV, TACAS, FM, ATVA), robotics (e.g., ICRA, IROS), AI (e.g., AAAI, IJCAI, ECAI) or machine learning (e.g., ICML, ICLR

PhD student on drive systems for vehicle applications

at the division are organized in two research units: power grid and components and electrical machines and power electronics. In the research unit on electrical machines and power electronics, we are about 30

PhD student position in neutron scattering studies of 2D hybrid organic-inorganic perovskites for energy applications.

the structural, electronic (and photoluminescent), and dynamical properties of the 2D HOIPs, to compare with the experiments. In particular, machine learning force field (MLFF) will be exploited to study finite

PhD student position in Formal Verification of Auto..

increasingly rely on data-driven learning-enabled components to perform a variety of challenging decision-making tasks. While indispensable for autonomy, learning-enabled components are unpredictable, e.g

PhD position in bioinformatics and artificial intelligence

environment, and, preferably, previous experience in working with machine learning and/or artificial intelligence. Good presentation and communication skills in oral and written English are also required