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modelling, machine learning, growth mixture modelling). Excellent skills in statistics and advanced quantitative data analysis, including strong skills in command driven programming languages (e.g., STATA, R
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are expected to submit a career development plan, specifying career goals and the competencies that the PhD fellow should acquire, no later than one month after commencement of the fellowship period. The
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status of cells real time. This person will also supervise current graduate students working on breast tumor innervation, given she has also gained experience in this area during his/her PhD tenure. In
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Pose EstimationStrong background in computer vision and machine learning applied to pose estimation and visual servoing; Experience with OpenCV, PCL (Point Cloud Library), PyTorch/TensorFlow, and 3D
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will work in close cooperation with staff and our current PhD students. PhD research fellows receive
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learning-based computer vision algorithms and software for object detection, classification, and segmentation. Key Responsibilities Participate in and manage the research project together with the PI, Co-PI
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date to be determined. Basic Qualifications A PhD related to programming languages by the start date. Experience in machine learning and formal verification. Individuals with a demonstrated track record
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representative work samples (e.g., journal paper, code repository, technical report, ontology/graph model) • 4 Reference letters, including one from candidate’s PhD supervisor • PhD/Master/Bachelor degree
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest in creative or artistic applications. Documentary evidence would be beneficial