21 phd-communication-and-signal-processing Postdoctoral positions at Chalmers University of Technology
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to work on topics at the intersection of applied probability and analysis. The group around Pierre Nyquist currently consists of three PhD students and is focused on questions in probability theory and
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of the Wallenberg Centre for Quantum Technology (WACQT, http://wacqt.se ). The core project of the centre is to build a quantum computer based on superconducting circuits. You will be part of the Quantum Computing
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effectively communicate scientific results both orally and in writing. You will also mentor and support PhD/master’s students working on related projects. Another important aspect involves collaboration within
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requires sound verbal and written communication skills in English. Swedish is not a requirement but Chalmers offers Swedish courses. You are expected to be somewhat accustomed to teaching, and to demonstrate
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their own research agenda within some of the department’s core themes: Digital transformation and innovation strategy – how organizations adapt their innovation processes and strategic priorities in response
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. PhD in a relevant field (e.g., logistics, supply chain management, operations management, engineering, or related disciplines). Experience with case study methodology and the ability to translate
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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focuses on the development of new materials and processes for electronics packaging and bioelectronics applications. The research of the electronics packaging group in the Electronics Materials and Systems
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diversity and consider equality and inclusion as fundamental aspects of all our activities. If Swedish is not your native language, Chalmers offers Swedish courses to help you settle in. Application procedure
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite