23 machine-learning positions at KTH Royal Institute of Technology

Postdoc in Machine Learning

programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job description We are looking for a Postdoc in Machine Learning who will conduct research focussed

Phd students in System Security, Formal Verification and Machine Learning

with a strong background in system security, formal verification, and/or machine learning to apply for two PhD positions, funded by Wallenberg AI, Autonomous Systems and Software Program (WASP

Postdoc in Algebraic Geometry applied to Machine Learning & Computer Vision

invites applications to a postdoctoral position supervised by Kathlén Kohn. The position focuses on research in applied algebraic geometry within machine learning and computer vision. The position is

Postdoc in autonomous performance management of networked services

made. The candidate should have strong research expertise from one or more areas: cloud computing and networking, machine learning/AI, statistics. We see that you have no problem collaborating with

Doctoral student in radar systems

techniques for modern antenna-array based radar systems. Different techniques, including machine-learning, will be investigated for advanced digital, analog and hybrid beam-forming concepts, and applied

Postdoc in 6G wireless communication and networking

theory, machine learning, signal processing, and optimization will likely play an important role. However, we are not looking for microwave engineers. The research will be carried out at the Division

Doctoral student in Transport Science

of new methods for data acquisition, AI, and Machine Learning, which is creating new opportunities in planning and urban and regional studies by the intersection of urban data science, technology, and

Support Coordinator at PDC

for Supercomputing in Sweden) hosted at KTH. It operates stateofthe-art computational and storage resources. Dardel is currently the fastest academic computer in Sweden, with four petaflops on the CPU partition and

Doctoral student in data driven predictive control for smart buildings

, optimization, and machine learning. They have proven to be efficient for complex systems with time varying dynamics. This Ph.D. project will be carried out within the framework of the Dig-It Lab competence

Postdoc in CFD simulation of hydrogen combustion

, data analysis and presentation of the result. The data analysis might include some coding in python for creating/modifying short scripts for using Machine -Learning or modal analysis techniques. What we