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are seeking a motivated PhD student to join our team working on realizing learning in novel physical materials, as part of a joint theoretical/experimental research project between AMOLF and the University
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description You educate and inspire the next generation of managers as they investigate the opportunities presented by data analytics (machine learning, deep learning, data mining) and new information
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join us as a PhD candidate. You will work in a highly interdisciplinary group, at the intersection of physics, machine learning and theoretical neuroscience. Our group is focused on investigating
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clinical experts. You will conduct new academic research combining machine learning and medical physics. Your research will be published in reputable peer-reviewed journals. Additionally, you will regularly
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PhD candidate will have: Master’s degree (or equivalent) in Human-Computer Interaction, Psychology, or Disability Studies Strong interest in accessibility, assistive technology, human-computer
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(PHM) for aerospace operations and maintenance, with strong expertise in sensor fusion, stochastic modeling, and machine learning. Your role: Design, build, and commission a laboratory test bench for
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-antibodies. You will focus on the identification of these antibodies by using mass spectrometry based de novo sequencing, machine learning and AI-tools to interpret the data. Your job The primary objective
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mass spectrometry based de novo sequencing, machine learning and AI-tools to interpret the data. Your job The primary objective of the project is to further develop mass spectrometry-based techniques
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Join us to decode how genetic variation reprograms brain cells and disrupts their communication using AI Job description We are looking for a PhD student to work at the intersection of machine
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University Medical Center Utrecht (UMC Utrecht); yesterday published | Netherlands | about 1 month ago
, epidemiologists, clinicians and lab researchers, with expertise in the field of prediction modeling, longitudinal data analysis, statistics, data science, machine learning, AI, organoid models and cystic fibrosis