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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
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(Chapter 7, Section 39 in the Higher Education Ordinance (1993:100)). Desirable qualifications Master’s degree in mechanical engineering or equivalent subject. Good knowledge of computer-aided engineering
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(AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians working collaboratively. Our focus is on developing practical methods that blend traditional disciplines
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. Merits for this position: PhD acquired within three years of last application date. Documented pedagogical experience. Experience in image analysis and/or computer vision, especially in the context
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, we offer a dynamic, collaborative ecosystem. The AI and Machine Learning in the Natural Sciences (AIMLeNS) lab is a tight-knit team of computer scientists, chemists, physicists, and mathematicians
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duties are to do defect analysis and development of new techniques for sample preparation and imaging (for instance using luminescence and microscopy). Also, computer simulations can be performed. Examples
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other relevant qualifications A high level of computer proficiency, particularly in advanced imaging and image analysis, FACS, in vitro and/or in vivo assays Very high motivation, ambition and enthusiasm
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equivalent. Specific knowledge of hydrology, urban water engineering, basic computer programming (e.g. Matlab or Python) and experience carrying out measurements of stream flow (or similar) are meritorious
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field measurements (e.g. related to soil–water processes or geophysical approaches), and basic computer programming skills (e.g. MATLAB or Python) are meritorious. Other important skills include
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requirement. A very good command of the English language, both written and spoken, is a key requirement. Experience in Federated Learning, Computer Vision, Image Analysis, Mathematics, and Mathematical