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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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energy, energy storage, electronics, medicine, sustainable manufacturing, etc. The main focus for the advertised position is novel machine learning method development. However, you will be part of a larger
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, diffusion models) to augment microscopy datasets Investigating domain adaptation techniques across different imaging modalities Collaborating closely with experimental partners to validate methods and
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of the documents referred to in III.2.3. are produced in a different language, a translation document into Portuguese or English shall be delivered. III.4. Applications that are not duly instructed or do not fulfil
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supervisors, from different universities: Dr. Georgios Tsaousoglou at DTU, and Dr. Maryam Kamgarpour at EPFL, Lausanne, Switzerland, with the opportunity to undertake an extended research stay at EPFL. Project
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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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will be involved in various international initiatives and engaged with different stakeholders. The candidate is expected to primarily but not exclusively deploy qualitative IS methods, with specific
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Organisation Job description PhD position: ML based implementation of constitutive behavior of stainless steel Metal forming is a widely used method to form steel products efficiently in mass
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would co-develop the research objectives and select the methods to be implemented with supervisory support. Some ideas to discuss include integrating repeat GEDI LiDAR surveys with time-series
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Organisation Job description PhD position: ML based implementation of constitutive behavior of stainless steel Metal forming is a widely used method to form steel products efficiently in mass