26 msc-in-statistical-learning PhD positions at Chalmers University of Technology in Sweden
Sort by
Refine Your Search
-
development (using both traditional signal processing and machine learning), antenna design, and system hardware development. We collaborate closely with clinical experts to develop innovative technologies
-
This PhD position is part of the WASP-WISE NEST project RAM³ – a multidisciplinary research effort at the intersection of machine learning and materials science. The project brings together PhD
-
Join the cutting-edge RAM³ project: Unlocking the Potential of Recycled Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics. We are offering a PhD position
-
effort at the intersection of machine learning and applied mechanics. The focus of this position is on extracting information about what a neural network has learnt in a symbolic and (human) interpretable
-
Aluminium through Machine Learning, High-Throughput Microanalysis, and Computational Mechanics” - a multidisciplinary research effort at the intersection of machine learning and materials science. This
-
the Swedish National Infrastructure for Computing (SNIC) and the Chalmers Centre for Computational Science and Engineering (C3SE). Learn more about the project and the research: Project overview Due
-
15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Engineering, Physics or Mathematics with strong
-
students pursue their Ph.D. in a similar area, which plenty of opportunity to collaborate and learn from and with peers. About the research project This ad is for a Ph.D. student researcher that will work in
-
team of over 15 full-time researchers offers a stimulating and supportive environment to learn and grow. Your profile Required qualifications: Undergraduate degree in Civil Engineering or a related topic
-
courses, including several master’s programmes. Learn more at: www.chalmers.se/en/departments/e2 Qualifications To qualify, you must: Hold a Master’s degree (or equivalent, 240 ECTS) in Engineering Physics