13 algorithm-development-"Multiple"-"Prof" "NTNU Norwegian University of Science and Technology" Postdoctoral research jobs at Harvard University
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is currently building and commissioning a network of calibrated multi-sensor observatory-class systems, and developing novel machine learning methods with the aim of collecting science-quality data
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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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deal of independence, can choose their research topics, and work with multiple faculty members. Candidates for this position must have completed their Ph.D. degree by the appointment start date
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. Successful candidates will be expected to contribute to technique development/material synthesis, plan and lead research projects, acquire and analyze experimental data, supervise and mentor undergraduate
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Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and
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the direct supervision of a postdoctoral fellow to study breast cancer initiation and progression using a newly developed mouse model of breast cancer together with primary patient samples. You will
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the pseudostratified architecture found in epithelial tissues, and how the architecture is exploited for various functions such as morphogenesis, organ development, and tissue fate. We use diverse model organisms
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. Successful candidates will be expected to contribute to technique development/material synthesis, plan and lead research projects, acquire and analyze experimental data, supervise and mentor undergraduate
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; acquire and analyze relevant data; supervise and mentor undergraduate students; prepare and submit peer-reviewed journal articles; and present their work at professional conferences. They will also be
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motivated Postdoctoral Research Fellow to develop and apply innovative, data-driven models for seismology, with a focus on developing cutting-edge foundation models. This is an exceptional opportunity