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Field
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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Fundamental Techniques in Table Representation Learning in collaboration with the University
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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Chemistry, Department of Chemistry – BMC The Department of Chemistry – BMC conducts research and education in analytical
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the design of innovative analytical and computational techniques to analyze,integrate and model multi modal data for the onset and progression of AMD. In doing so,the successful postdoctoral fellow will
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Applicants should hold a relevant MSc degree in electronics, electrical engineering, computer engineering, or related fields. Required Qualification: Solid background in digital CMOS design and deep learning
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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of the GAG biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working
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used to develop networks capable of self-learning and self-optimisation, adapting to real-time changes in traffic and demand. The successful candidate will contribute to designing solutions that optimise
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background in CMOS/VLSI design, computer architectures (preferred RISC-V architecture), and deep learning principles. Experience with industry-standard EDA tools such as Cadence suite: Genus, Virtuoso, Spectre
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/thesis: Challenges and opportunities with remote sensing and machine learning in forestry Research subject : Soil science Description: WIFORCE Research School Do you want to contribute to the future
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data is lacking. With the DataLibra project, we aim to close this gap, by developing AI models and tools for structured data (Table Representation Learning), to help organizations, of any size, domain