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Field
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will be curious, analytical, and motivated to tackle real-world problems at the intersection of energy, health, and climate resilience. The research will make a significant societal and environmental
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areas: Developing and training robust machine learning surrogates to replace computationally expensive high-fidelity simulations, enabling exploration of vast design spaces. Formulating optimization
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looking for checkboxes; we’re interested in who you are and what you bring. Do you recognize yourself in this? Strong analytical and interdisciplinary mindset – You enjoy bridging medical statistics and
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, inspection histories, operational performance data, hyperspectral imagery, train-borne video analytics and satellite soil-moisture products to build predictive models of vegetation-driven and water-driven
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(MPC) and Reinforcement Learning (RL) have proven effective in isolated studies, their widespread deployment is hindered by the lack of interoperability, the high cost of model creation, and data
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Amsterdam Rotterdam); teach seminars and/or practical for bachelor and master students; supervise bachelor and master student projects; present data at local, national and international scientific meetings
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care about creating a positive, respectful, and stimulating environment. We value communication and collaboration and a workplace that promotes learning and development for all employees. We are also
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The doctoral student will be employed at Mid Sweden University as part of the Swedish research school for excellence in Arctic and Antarctic Learning (SEAL) , which offers an internationally competitive
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research. You will strengthen the data science and machine learning activities of IAS-9 by developing core AI methods with applications to electron microscopy and materials discovery. You will work in a team
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based