15 learning-"https:"-"https:"-"https:"-"https:" Postdoctoral positions in Switzerland
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(or similar): Coherent diffractive imaging, especially ptychography. Sparse sensing, optimization, or Bayesian experimental design. Machine learning for imaging. Synchrotron experiment experience. Semiconductor
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datasets with multi-omics profiles of tumors from previous studies Developing new machine learning models through collaboration with the Swiss Data Science Centre Establishing data analysis pipelines
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disease progression. However, the mechanisms by which peripheral neural circuits detect changes in tissue state and instruct immune cell function remain poorly understood. The successful candidate will lead
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interest in contributing to both the conceptual and empirical dimensions of research Proficient in, or willing to learn, programming languages (e.g. MATLAB, Python, R) Experience with one or more of the
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physiological acquisition systems; real-time data acquisition; motion capture or positional tracking; Bayesian or hierarchical modeling; reinforcement-learning models; effort-discounting or decision-making models