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Field
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) scientific studies Experience with relevant field data collection methods (e.g. chamber- or eddy covariance-based C flux measurements, biodiversity sampling methods) Computer programming skills (e.g. Matlab, R
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oral communication skills in English. Meritorious: Knowledge and experience in: working with statistical methods and analyses. programming and data processing. We place great emphasis on personal
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the position and why you are especially qualified for it. Your workplace You will be employed in the Reasoning and Learning Lab (ReaL), Division of Artificial Intelligence and Integrated Computer Systems (AIICS
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Computer Science Electrical and Computer Engineering Mechanical Engineering Applied Mathematics Applied Physics Statistics and Optimization A strong background in robotics, machine learning, and control is essential
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admission process. Do not include recommendation letters. The application may need to contain the following: A secondary research text authored by the applicant. It is mandatory to submit a secondary research
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doctoral education. The PhD position is linked to Section 1 at the Faculty of Odontology (Oral Biology and Pathology) with collaboration within Section 2 (Maxillofacial Surgery and Materials Science and
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conducting experiments at SLU's experimental facility Lövsta, as well as field work at chicken farms and slaughterhouses. A large part of the working time will be spent compiling, statistically processing and
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. Your profile You have documented expertise in marine ecology and computer vision and machine learning methods for video-based fish monitoring. You have excellent IT skills and experience in handling
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: (i) development of low impacting functional inks, (ii) development of bioderived films, (iii) development of processes for the printing of the developed materials and (iv) optimization of processes and
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of Electrical Engineering. Project description: Autonomous vehicles for mining and mobile robotics for industrial processes require complex motion planning as well as safe model-based predictive control and