1,115 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions in Spain
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to support future project maintenance. Agile methodologies: Actively participate in team ceremonies (Daily Stand-ups, Sprint Planning, Retrospectives). Requirements: Bachelor's Degree in Computer Engineering
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the development and assessment of neurotechnology aimed for invasive brain-computer interfaces. In particular, the work will include in vitro assessment of the performance of electrophysiology neural
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: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science, Gaming Engineering or a related discipline. · Knowledge: Strong coding skills in Python and knowledge in materials
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? Professional experience You have experience with computer programming Experience with biological data analysis is a plus Education and training You have a bachelor’s or master’s degree in bioinformatics
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Cluster hire of PIs and postdocs in the fields of evolution, biodiversity conservation and ecology, genetics, neuroscience, brain-computer interface, human disease mechanisms and Interdisciplinary
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learning and the use of robust statistics. This work is naturally extended to studying physics prospects for the next generation of detectors. IFAE is supported by its own PIC computing center, a Tier1 LHC
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characterize new reticular materials (COFs), and use them as precursor for the generation of new polymers via Clip-off chemistry. The candidate will acquire a great experience in supramolecular, reticular and
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. Knowledge and Professional Experience: Interest of learning (S)TEM, EM related spectroscopies and in-situ techniques (use of gas and/or liquid, bias and heating STEM sample holders). Previous experience
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Multitasking and flexibility are instrumental for the success on the role Attention to details and positive attitude are key Willingness to learn and open to feedback Please note that you must have the right
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(S)TEM. Requirements: Education: MSc in Physics, Materials Science, Nanoscience, Computer Engineering, Data Science. Knowledge: Deep expertise in electron microscopy, particularly STEM and FIB methods