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Field
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conferences. support the teaching activities at the faculty (up to 10% of the time). What we ask of you A PhD in Machine Learning, Computer Science, Mathematics, Statistics, Physics or a closely related field
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transport proteins in lipid membranes. Furthermore, the ultimate long-term goal is to integrate these cells in a dialysis machines. The objectives for this position are to: Formulate synthetic cells with
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/postdoc-ub4h-digital-technologi… Requirements Specific Requirements A PhD in educational sciences, engineering education, learning sciences, or a related discipline. Knowledge of hydrogen technology or
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at interdisciplinary conferences alongside a team of psychologists, historians, and computer scientists. What do you have to offer Must-have: You have completed a PhD in psychology, computational social science
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and digitizing archival data, strong knowledge of causal inference methods, good command of R and Python. Knowledge of machine learning methods is an asset. Strong command of English; command of either
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. Background: You hold a PhD in Computer Science, Machine Learning, Electrical Engineering, Embedded Systems or related fields. Core Expertise: Strong expertise in Federated Learning and/or Continual Learning
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outcomes under different market design scenarios. The research will combine machine learning, stochastic optimization, and agent-based modelling with behavioural experiments. Case studies from emerging
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to develop synthetic cells that mimic tubular function by integrating transport proteins in lipid membranes. Furthermore, the ultimate long-term goal is to integrate these cells in a dialysis machines. The
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or continual learning paradigms Research Statement. Two reference letters (one from your PhD supervisor). Please contact Dr. Özlem Durmaz Incel if you have any additional questions via the following
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biomedical image processing. Within the scope of machine learning and computer vision, there will be freedom to suggest your own research directions, and to become acquainted with new techniques and approaches