17 cognitive-radio-networks Postdoctoral research jobs at Chalmers University of Technology in Sweden
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, diversity, and gender equality, supported through networking and mentoring activities. A friendly and inclusive working atmosphere, both within the research group and across Chalmers. About the research
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Join a young team with a strong national and international network in the field of the rapidly expanding area of metal additive manufacturing at Chalmers University of Technology ! This postdoc
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network of national and international collaborators. Project overview The aim of this two-year project is to validate and further develop advanced numerical models (originally developed at Chalmers
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, and engage with a vibrant network of national and international collaborators. The recruited candidate will work in the AIMLeNS lab lead by Assoc. Prof. Dr. Simon Olsson at Chalmers University
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entities Preferred qualifications Experience in biomechanics, particularly head/skull injury mechanics or impact biomechanics Knowledge of material characterization techniques and experimental mechanics
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, particularly head/skull injury mechanics or impact biomechanics Knowledge of material characterization techniques and experimental mechanics Familiarity with optimization algorithms and design of experiments
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education in engineering, science, shipping and architecture. With scientific excellence as a basis, Chalmers promotes knowledge and technical solutions for a sustainable world. Through global commitment and
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in English (spoken and written); knowledge of a Nordic language is considered a merit Ability to work effectively in an international and interdisciplinary environment *The doctoral degree must have
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and written English Strong academic record with publications or clear potential for publishing in top-tier journals Advanced knowledge of one or more qualitative and/or quantitative research methods
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digital twin framework, adaptable to: The level of detail available for ship modelling, The quality of risk-related data, and Quantified model and data uncertainties. The project will advance knowledge