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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
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and/or practical experience with measurement techniques in fluid dynamics and heat transfer. Contract terms The position is limited to four years, with the possibility to teach up to 20%, which extends
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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
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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
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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
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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
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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
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accepted. The following experience will strengthen your application: Familiarity with Federated Learning We value a collaborative attitude and an interest in working both in teams and independently. Self
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the possibility to teach up to 20%, which extends the position up to five years. What we offer As a PhD student at Chalmers, you are an employee and enjoy all employee benefits. Read more about working at Chalmers
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and enjoy all employee benefits. Read more about working at Chalmers and our benefits for employees. The position is limited to four years, with the possibility to teach up to 20%, which extends