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the Swedish Center for Sustainable Hydropower (SVC). SVC promotes collaborative research across universities and industry to support the future of hydropower. Simulations will be performed using resources from
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diversity brings to the organization. Please apply by clicking on the Apply button at the bottom of the ad. Applicants are requested to the application resolving CV, cover letter , a copy of a relevant essay
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minimum of one year at second-cycle level. Applicants must submit: a CV a two-page proposed research statement copies of degrees and transcripts of all academic records copy of the MS thesis at least two
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if supporting documents are discovered to be fraudulent. Submission of false documents is a violation of Swedish law and is considered grounds for legal action. (A) and (B)can only be certified by
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on the following criteria: Knowledge in electric power engineering, power electronics, and power system analysis Experience in modelling, simulation, and experimental work Proficiency in Swedish and English, both
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present research interests. CV. Attested documents (academic transcripts, diplomas, and evidence of relevant teaching or industry experience). Copy of your Master’s thesis. If not yet available, submit your
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simulations to explore which gene regulatory network architectures are necessary for robust regulation and effective communication between compartments. A third possibility is to simulate the evolutionary
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of scientific data, e.g. from image acquisition modalities or scientific simulations. Efficient algorithms are at the core of most of these data analysis and visualization applications. The focus of this Ph.D
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the different organelles. Another approach is to use Monte Carlo simulations to explore which gene regulatory network architectures are necessary for robust regulation and effective communication between
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ROS Practical experience in hardware and simulation-based implementations Fluency in both written and spoken English Previous experience in robot learning research will be considered a strong merit