Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
Are you excited by the mechanisms of neurotransmission and behaviour and looking for a new opportunity? We are looking for an enthusiastic, inquisitive and motivated post-doctoral researcher to join
-
motivated researcher with a strong background in computational modeling, system identification, and uncertainty quantification for civil infrastructure. The successful candidate will join the Risk Assessment
-
machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields, including robotic control, fluid mechanics and
-
integrate in vivo mouse models and proteomics via mass spectrometry to uncover mechanisms of immune reprogramming and therapeutic response. Minimum Qualifications: PhD in Biomedical Sciences, Bioengineering
-
contribute to the teaching activities of the section of Mechanical Engineering by teaching 1-2 courses per semester. You will focus on developing and extending in-house computational codes based on open-source
-
candidate would become an ARIA R&D creator. Responsibilities: Conduct foundational research on aggregation mechanisms, including: for-mal modeling and axiomatic analysis, computational complexity and algo
-
, Mechanical, Thermal Engineering or Computer Science. Experience Experience in conducting high quality academic research. Demonstrable ability to write material of a quality commensurate with publication in
-
& Perception Laboratory (NA&P Lab), led by Dr. Sabine Kastner at the Princeton Neuroscience Institute. The lab studies neural mechanisms of cognition in the primate brain. Intracranial recordings from human
-
candidate would become an ARIA R&D creator. Responsibilities: Conduct foundational research on aggregation mechanisms, including: for-mal modeling and axiomatic analysis, computational complexity and algo
-
into two main areas: (1) material development and characterization to ensure optimal sensing and mechanical performance, and (2) structural evaluation of SS-FRCMs under environmental stressors such as freeze