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Amsterdam Rotterdam); teach seminars and/or practical for bachelor and master students; supervise bachelor and master student projects; present data at local, national and international scientific meetings
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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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candidate, you are at the core of the project. You will perform all wet lab analyses using advanced techniques such as cell culture, reporter analyses and RNA-sequencing. You will perform the data analysis
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to learn more about the project, and perhaps our group? Feel free to browse our webpages: About our department: QCE department . About our group: Computer Engineering Lab . Job requirements For this position
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supported in learning new techniques and broadening your mathematical background. You will have the opportunity to present your work at both national and international conferences and workshops, for which
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, silicon-proven AI/ML accelerator for transmitter error correction (digital predistortion/calibration). Your work will sit at the intersection of machine learning, DSP, and digital IC design, and you will
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You will join the “Professional Learning & Technology” (PLT) section of the Faculty of Behavioural, Management & Social Sciences. The PLT section specializes in research on professional learning in and
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industrial partners across Europe Network-wide training schools and workshops Supervision by leading experts in the field A personalized Career Development Plan Challenge-based learning principles Where
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-scale compound drivers. We will leverage machine learning methods to bridge the gap between drivers at coarse model resolutions and impacts captured by high-resolution observations. Job description Arctic
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on AI-supported decision-making that contribute to the empowerment and democratic participation of citizens. The project addresses real-world challenges across domains such as healthcare, mobility