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laboratory team is likewise highly recognized for its research in computer vision and neuro-inspired artificial learning. Both teams have been collaborating for four years on projects at the interface between
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, communication systems, and machine learning. Are you motivated to take a step towards a doctorate and open up exciting career opportunities? As a PhD Candidate with us, you will work to achieve your doctorate
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-pathogen interactions and feedback, using a combination of quantitative imaging, microfluidics, statistical analysis and machine learning tools. A specific focus will be put on discovering biophysical
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mixed reality (MR) strategies to blend information derived from machine learning and computer vision processes to the workers' expertise. The objective of this project is to develop and evaluate MR
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synthetic biology, machine learning (ML), and ultrahigh-throughput screening (microfluidics) to discover new enzymes and bioactive molecules with applications in biotechnology, medicine, and sustainability
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consortium, 23 partners across Europe, aims to unlock the hidden potential of global metagenomic sequence space using a combination of synthetic biology, machine learning (ML), and ultrahigh-throughput
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an ARC Linkage Project focused on developing an autonomous system for detecting and quantifying structural damage in infrastructures (e.g., bridges, grain silos) using computer vision, digital twins, and
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: A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field Prior experience in computer vision, deep
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be expected to teach advanced courses in Artificial Intelligence—particularly in machine learning, statistical learning, natural language processing (NLP), symbolic AI, computer vision, and related
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Technology has a vacancy for 1 PhD Research Fellow in Privacy Preserving Machine Learning. The successful candidate will be offered a 3-year position. Are you motivated to take a step towards a doctorate and