145 algorithm-development-"https:"-"Simons-Foundation" Fellowship positions at Harvard University
Sort by
Refine Your Search
-
Engineering, to develop an independent research project within the scope of the lab’s research focus. In addition to carrying out machine-assisted visualization research, the successful candidate will be
-
) or indirect (i.e., from an awardee institution) funding for trainees at the postdoctoral level or identify programs that focus on educational developments such as curricula development, training or retention.
-
https://d3.harvard.edu and https://d3.harvard.edu/lish/ . Research Focus: Postdoctoral Fellows at D^3 will conduct research at the intersection of innovation, digital transformation, and artificial
-
David Rudner’s lab at Harvard Medical School in Boston Massachusetts. Work in the Rudner lab focuses on fundamental questions in bacterial cell biology and development: How is information transduced
-
the importance of design and innovation on value creation for stakeholders. For more information on D^3/LISH , please visit https://d3.harvard.edu and https://d3.harvard.edu/lish/ . Research Focus
-
information on D^3, please visit https://d3.harvard.edu . Business, the global economy, and societies around the world are facing dramatic upheaval as a result of rapid technological change driven
-
psychological assessments. Training in professional skills development will also be offered, including guidance in writing grants and papers, assistance in building a professional network, supervising trainees
-
. The successful candidate will work with Dr. Devlin to develop an independent research project within the scope of the lab’s research focus. In addition to carrying out bench research, the successful candidate will
-
Salary Range This position is salaried and benefits eligible. Information regarding postdoctoral fellow salary, which is determined by the number of years post PhD, and benefits can be found at https
-
recordings, behavioral training, and visual experimentation, while also developing and testing deep neural network models of visual representation. In short: experiments first, models second. Current and