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The Steinmetz Lab (steinmetzlab.com) at UC San Diego is seeking talented and motivated post-doctoral researchers to work in immunoengineering and immunotherapy targeting cancer, cardiovascular and
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techniques from statistical physics, Bayesian inference, and complex systems theory to address challenges posed by noisy and incomplete data. Depending on the results obtained in the first year, the post can
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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statistical analysis and modeling techniques such as Gaussian process modeling, data assimilation, and Bayesian analysis; and 4. Open-source scientific software development. Expertise in computational
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the voluntary adoption of effective bycatch reduction strategies in targeted fisheries. There will also be opportunities to contribute to writing research proposals and mentoring graduate students. Required
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with statistical modeling (ideally Bayesian statistics) • Proficiency in Fortran, R, Python, Matlab, or ideally other common languages (e.g., C/C++) Strong computational skills Strong oral and written
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, technical and mission-defining analyses of the Moon, NEAs, Phobos and Deimos (Target Bodies) for relevant NASA programs, planning and space missions, including a Mars forward focus. The research topic areas
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staff position within a Research Infrastructure? No Offer Description The Centre of Excellence in New Target Discovery (CENTD) is a multidisciplinary center studying molecular targets of inflammatory
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on-demand control of genetically targeted neurons and astrocytes.More information about the lab can be found at: https://people.eecs.berkeley.edu/~chunlei.liu/ Key Responsibilities Design and conduct
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on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have