Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
engineering, mechanical engineering) Publications in peer-reviewed journals Expert in powder-feed direct energy deposition systems Experience in materials characterization instruments (scanning electron
-
Associate Professor Thor Grünbaum. The larger project develops and tests a new theory of basic cognitive selection mechanisms by combining methods and perspectives from experimental psychology, cognitive
-
. This work is part of European Union’s Quantera Program project “MQSens: Quantum Sensing with Nonclassical Mechanical Oscillators”, where opto-/electromechanics is utilized to explore how quantum protocols can
-
National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 44 minutes ago
is reproduced in the NASA Ames Electric Arc Shock Tube (EAST) facility, and is used to test models developed to predict the heating mechanisms. The primary models employed are the DPLR computational
-
formation, statistical astronomy, and transient science. Applicants may work with the Department's distinguished faculty and research staff. For a full list of department members and activities, see https
-
rehabilitation. The successful applicant will have the following technical experience in: PhD degree in Electrical, Mechanical, or Material Engineering (or related field) OR 3-5 years of industry experience
-
intracellular spaces. We are looking for individuals with strong background in small molecule and polymer synthesis and their characterization, experience in characterizing the mechanical and surface properties
-
mechanisms of meiotic chromosome segregation using Drosophila oocytes as a model system (http://ohkura.bio.ed.ac.uk). We are looking for an enthusiastic and talented researcher to study spindle regulation in
-
currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
-
currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We