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variability in risk factor susceptibility, treatment response, disease pathogenesis, and clinical diagnosis (biostatistics, machine/deep learning), ii) Investigating causal processes and disease mechanisms
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the driver to actively participate and accept the interventions. A key component in the project will be to practically test feasibility and assess the performance of algorithms and hypotheses in test track
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. Position description Construction industry is one of the biggest contributors to waste and carbon emission and this sector is at a crossroads. Unless major changes, the industry risks failing to meet the
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closely with a co-supervisor at the Division of Material and Computational Mechanics. The NEST-WISE project offers a vibrant collaborative environment and close interaction with academic and industrial
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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
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future product owners and users is a key factor to the success of these projects. In this, you will work closely with other LTU researchers and doctoral students. Duties As a PhD student, you work towards
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working with both academic and industrial partners in Europe. Hence, collaboration with the software and automation industry in the form of both future product owners and users is a key factor to the
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factor to the success of these projects. In this, you will work closely with other LTU researchers and doctoral students. Duties As a PhD student, you work towards a Doctoral degree as the final goal
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working with both academic and industrial partners in Europe. Hence, collaboration with the software and automation industry in the form of both future product owners and users is a key factor to the
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research activities in stormwater management. The research is both theoretical and experimental with elements of computational technology and mathematical modelling and is based on close collaboration with