15 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"ETH-Zurich" Postdoctoral positions at Harvard University
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Dana Foundation Professional Development Awards Eligibility: Applicants must be currently affiliated with an academic or non-profit institution in the United States and enrolled in a training
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FAS Office of Postdoctoral Affairs: Postdoctoral Awards for Professional Development (PAPD) Deadline Month: This program is currently on pause. Description: These awards are designed to support the
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institutional leaders to design, implement, strengthen, and broaden postdoctoral fellowship experiences for scientific advancement and professional and career development in the Harvard Longwood community
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the intersection between quantum information and particle physics. The successful applicant will work in Professor Carlos Argüelles’ group on the development of new algorithms to encode and process particle physics
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of support for the career development activities for underrepresented postdoctoral fellows in a degree-granting institution (an institution includes its affiliated graduate and medical schools, hospitals and
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contribute to publications and will have opportunities to take on leadership roles within collaborative projects. Research topics include, but are not limited to: Galaxy formation and evolution across cosmic
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, highly organized research assistant seeking experience in cutting-edge technology development and eager to make discoveries with molecular and synthetic biology techniques. During this project, you will
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that are covered include (as examples) postdoc salary, the salary of a technician directly supporting the postdoc’s project, professional development opportunities, and/or specialized research supplies needed
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—are intended to foster the early career development of researchers who have transitioned or are transitioning from training environments in the physical/mathematical/computational sciences or engineering into
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. ● Demonstrated expertise in causal inference, with interest in methods development. ● Experience with statistical and ML methods, including at least one of the following: Bayesian methods, deep learning