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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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measurements in animals and programming with Python/Matlab is a meritorious achievement. Documented experience with calcium imaging and/or optogenetics, as well as behavioral measurements is particularly
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and programming experience (e.g. R, Python) are required. Experience with psychophysiological methods, such as eye tracking and skin conductance, is advantageous. Excellent academic merits, including
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publication record in reputable peer-reviewed journals is highly desirable. Proficiency in programming, particularly in R, Python, or other relevant languages, is required. Qualified candidates should also meet
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and production development, mechanical engineering, industrial engineering, or equivalent. experience in programming, preferably Python. fluent in spoken and written English. proficiency with mechanical
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experiments Documented expertise in data analysis using scripting (ideally python-based) Experience carrying out SAXS/WAXS experiments at large scale facilities Working experience with soft matter and/or
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., Computer Science, Cognitive Science, Human Computer Interaction, Human Robot Interaction or Artificial Intelligence. experience in programming, preferably Python. fluent in spoken and written English. It is
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, demonstrated experience of coding in programming languages such as R and Python is considered particularly advantageous. Examples of computationally intensive methods central to IAS and IDA are data-driven text