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experience and enhanced potential to receive an ERC Starting Grant in the future. Open to both PhD (natural sciences) and MD (medical sciences) holders. From a variety of academic backgrounds: molecular
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algorithms for the scanner using machine learning and deep learning. Qualifications: The position requires some background in machine learning, optimization, and deep learning. Some familiarity with MR physics
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Preferred Qualifications: PhD in physics, bioengineering, electrical or mechanical engineering, computer science, or a related field with experience building imaging instrumentation and interest in biological
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clinical pulmonologists and immunologists to study the molecular mechanisms that underly airway tissue homeostasis and asthma pathogenesis. In addition, our group aims to develop new computational algorithms
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Requirements Required skills, abilities, and knowledge: Recent or soon-to-be completed PhD (within the last 0-5 years) by the start of the appointment in computer science, electrical engineering, applied
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(intracranial and scalp EEG) and MRI data sets. Develop and implement algorithms for data processing and interpretation. Collaborate with clinicians and researchers to design studies and analyze results. Present
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specific work experience is required for this position. Skills: Not Applicable Driver's License: A driver's license is not required for this position. More About This Job Preferred Qualifications: PhD in
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. This project employs massive-scale genome sequencing, data that will enable a wide range of novel, independent projects. The project also involves a substantial theoretical component including algorithm
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on their research and innovation campus. Required Qualifications - PhD and/or MD in Computational Biology, Bioinformatics, Genomics, Biology, Data Science, Computer science or other related fields. PhD must be
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algorithm-based technologies in service occupations, with a focus on how collective bargaining and other forms of collective worker voice influence these strategies and worker outcomes. The US research will