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consumers. You'll gain deep interdisciplinary experience—combining multiple data layers and approaches including bioinformatics, machine learning, food safety management, regulatory science, genomics and user
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applications Strong analytical and problem-solving skills Good communication skills and ability to collaborate across disciplines Motivation to make a real-world impact in sustainable energy and industrial
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, the CAPeX approach to finding new electrocatalytic materials for energy conversion reactions uses state-of-the-art machine learning techniques, but experimental feedback is needed to improve the models and
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PhD scholarship in Runtime Multimodal Multiplayer Virtual Learning Environment (VLE) - DTU Construct
behavior and provides active personalized learning for improved instant decision making. Key beneficiaries are expected to be construction industry stakeholders, for example, project owners, architects
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into the enzyme-substrate interaction in the same set of enzymes. Further, there will be collaboration with a PhD student from NTNU working with similar analytical methods on another class of carbohydrate-active
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of the research group. Desired qualifications and skills: A relevant background in aquatic biology, animal physiology or a related field. Good skills for laboratory-based analytical tools. Practical experience
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behaviour and provides active personalised learning for improved instant decision making. Key beneficiaries are expected to be construction industry stakeholders, for example, project owners, architects, engi
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) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness of the assessment. All components assembled
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(e.g., Kalman Filter) or Machine Learning models. These tools will be integrated with physics-based models of environmental loading (waves and wind) to enhance the accuracy and robustness