72 phd-mathematical-modelling-ecological-modelling Postdoctoral research jobs at Technical University of Denmark in Denmark
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production and quality control will help save natural resources as well as reduce waste material and energy consumption. Formulation and test methods using mathematical modelling and prediction tools. Fouling
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Job Description Are you worried about the coastal regions in an era of climate change and plastic pollution? Do you want to play a part in the development of a novel numerical model that can shed
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interdisciplinary team, you will break new ground at the absolute frontier of what is possible. Responsibilities Your overall focus will be to evolve and then engineer non-model autotrophic bacteria for expanded
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for industrial decarbonization with emphasis in system development, modelling, optimization and validation, and focus on: Develop thermally integrated storage and conversion systems, including Carnot batteries and
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language models (LLMs) for educational purposes. Furthermore, the right candidate has a deep understanding of pedagogical research, with focus on how educational processes can be facilitated by AI. The role
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-world medical applications? Do you want to design next-generation protein therapeutics using cutting-edge generative models and validate them in the lab? Join a collaborative postdoc project at DTU
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strategies for conventional HVAC systems that condition entire indoor spaces using existing thermal comfort models, which could improve the performance of existing buildings and HVAC systems. The work will
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change (sea level rise and increased storminess in Northern Europe), coastal erosion is expected to potentially worsen. State-of-the-art practical engineering models for predicting sand and particle
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modelling. It is expected that the degree of involvement in meetings and organisational tasks related to research projects will increase steadily during the employment. The following qualifications are highly
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers