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Stockholm University, Department of Mathematics Position ID: 2543-PHD [#27194] Position Title: Position Type: Student programs Position Location: Stockholm, Stockholm 106 91, Sweden [map ] Appl
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. Your qualifications You have graduated at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics, with a minimum of 240 credits, at least 60 of which must be in advanced
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or employment: Employment (4 years of PhD-studies) Starting date: According to agreement. Application: Click the “Apply” button to submit your application. The deadline is 2026-02-10. To qualify for third-cycle
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educational programs in Computer Science, we are now seeking a PhD student with a focus on Neuro-Symbolic Graph Transformation. The Department of Computing Science has been growing rapidly in recent years, with
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to energy systems and heating, ventilation and air-conditioning systems (HVAC) in both the residential and the industrial sector. As a PhD-student you will be part of two main research areas, comfort cooling
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English. The PhD must have involved numerical modelling. It is desirable to have documented knowledge from their university education in: Mathematics, especially differential equations. Numerical methods
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subject: Technology/Forest management/Biology Description: The Department is looking for a PhD student within the area of remote sensing of forest. Using remote sensing the PhD student will develop methods
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, Electrical Engineering, or Applied Mathematics with a minimum of 240 credits, at least 60 of which must be in advanced courses in Computer Science, Electrical Engineering, or Applied Mathematics. Alternatively
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collaboration with Lund University. The candidate is expected to have a strong mathematical background particularly in stochastic modeling, optimization, and reinforcement learning. As a PhD student, you devote
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team of atmospheric modellers at the department. Qualification requirements Requirements: The applicant must have a PhD degree in atmospheric science or simular. Applicant must have work life experience