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We are seeking a highly motivated and dynamic PhD student, who is enthusiastic about neural dynamics and sensory processing. The focus of our research is how the combination of sensory signals and
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biology: “How can cells control processes in space and time to achieve a fine-tuned regulation? To uncover this fundamental question, we aim to understand the formation of liquid, biomolecular condensates
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their universities. To be considered the applicant must have a basic education at master's level (corresponding to the 3 + 2 Bologna process) have received the grade of 10 (or equivalent) for the master's thesis
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estimation of rotating tools. Direct tool wear characterization will be based on optical measurement systems and data processing to achieve wear feature recognition and quantification. Indirect tool wear
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: They are responsible for the central tasks of storing and processing quantum information. The memories must be optically active so distant nodes in a network can be entangled via single photons emitted by the memories
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the Loft group is particularly focused on understanding how the adipose tissue serves as a critical signaling hub in the context of metabolic diseases, such as MASLD and cardiovascular diseases. For this, we
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signal processing, with experience in machine learning, deep learning, or AI methods. Familiarity with semantic segmentation, anomaly detection, or pattern recognition techniques is highly valued. Sensor
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for physiological signal recording. An ability to work independently and collaboratively across disciplines will be essential. Excellent communication skills in English, both written and spoken, are required, and
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disease as well. Description of the candidate: The successful candidate is expected to hold: A master degree in biomedical engineering or equivalent. Excellent programming and signal processing skills
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estimation of rotating tools. Direct tool wear characterization will be based on optical measurement systems and data processing to achieve wear feature recognition and quantification. Indirect tool wear