19 parallel-processing-bioinformatics-"Multiple" PhD scholarships at Linköping University in Sweden
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treatment. It is advantageous if you have previously worked with massively parallel sequencing (NGS), both in the laboratory and/or with bioinformatics, for example Single Cell RNAseq. It is also advantageous
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application! We are looking for a PhD student in Wireless Communication and Computer Vision. Your work assignments Point clouds (PCs) are sets of three-dimensional (3D) data points and their attributes
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bioinformatics, the project will expand our knowledge of mRNA regulation in the adaptive immune system and identify potential molecular targets for therapeutic interventions in inflammatory disease. As a PhD
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, localization, and sensing, with a focus on developing next-generation multiple-antenna systems while optimizing overall system performance. As a doctoral student, you devote most of your time to doctoral studies
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application! We are now looking for a PhD in Environmental Science with focus on degradation of organic pollutants in biogas processes. Your work assignments The position for a doctoral student is announced as
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application! We are now looking for a PhD in Environmental Science with focus degradation of organic pollutants in biogas processes. Your work assignments The position for a doctoral student is announced as
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departmental duties, up to a maximum of 20% of full-time. Your qualifications We are searching for someone with a Master’s degree in computer science, media technology, computer engineering, human-computer/robot
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computer graphics. Great emphasis will be placed on personal qualities and suitability. Your workplace You will belong to The scientific visualization group that is a part of Media and Information
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application! A brighter future! How does lighting design affect future design and product development processes and how digital tools such as VR/MR can contribute to experimentation and evaluation. Your work
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application! Your work assignments Our research projects focus on distributed sensing, hardware-efficient signal processing, robustness and resilience, and communication-efficient decentralized machine learning