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(lth.se). We invite applications for one to two PhD positions dedicated to developing methodologies for the automated analysis and design of first-order optimization algorithms. Such algorithms form
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kind in Sweden and, together with MemLab – the industrial membrane process research and development centre – offers excellent infrastructure for developing and optimizing membrane processes from lab
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genetic data (e.g. from genotyping). You will implement and evaluate selection methods: Test and optimize new methods for precision breeding in practical or simulated improvement programs. You will work
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unwanted effects from so-called concomitant gradient fields. You will also develop software to facilitate experimental design. This includes numerical optimization of the instructions that control the MRI
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driven analysis of electron density to reduce the computational costs of multiconfigurational calculations. Design and implement optimization procedure for model potentials and atomic basis sets
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KAU whose mission is to optimize the circularity of bioeconomy); contribute to teaching and education in degree programs and to develop your own pedagogical competence; contribute to the ongoing
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on interpretable, learning-based stochastic optimal control for over-actuated electric vehicles—vehicles with more actuators than degrees of freedom, which enable sophisticated control strategies but also increase
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polynomial equations, and optimization. In this project, we will also explore new methods for 3D modeling and sensor position estimation that operate directly on sensor data. Here, we will also use new so
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activities. You will also be located a minimum of 20% in the food industry, with placement at the company Lantmännen. Detailed description of the work duties, such as: Optimization of wholegrain content in
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on how your research can be further developed into innovations. You are interested in driving the integration of methods in artificial intelligence (AI) and machine learning (ML) to improve and optimize