Sort by
Refine Your Search
-
Listed
-
Field
-
preferred. Proficiency in computational tools such as MATLAB, Python, R, or machine learning applications in immunology is desired. Candidates should have a PhD in Chemistry, Chemical Engineering
-
Postdoctoral Associate to investigate the neural mechanisms underlying continual learning in humans. The successful candidate will develop computational models examining the tradeoff between task
-
a related field, and should demonstrate strong expertise in at least two of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method
-
via autophagy and lysosomal targeting in learning and memory and disease models using rodents and iPSC-derived cell cultures. These mechanisms will be investigated in both healthy conditions and
-
well as market and organization considerations. Education: Ph.D. in machine learning, computer science, engineering, science or related technical discipline. Experience: Expertise in developing and training AI
-
optimize machine learning (ML) and AI-driven climate risk models for the ClimateIQ project. This position will refine ML approaches to provide high resolution climate hazard information and improve decision
-
ecological systems with frequency-dependent selection. Planned projects use dynamical systems, stochastic differential equations and agent-based models, statistical methods for parameter inference, network and
-
and multimodal perception/behaviors, generative diffusion models, cloud-based computer graphics, and neural rendering (e.g., neural radiance fields and 3D Gaussian splatting). The NYU ICL
-
Details Posted: 31-Mar-25 Location: New York, NY Categories: Academic/Faculty Internal Number: 165613 We are seeking an outstanding scholar with expertise in hydrological and hydrodynamic modeling
-
/photometric data analysis, and spectral modelling, are strongly encouraged to apply. Successful candidates will be encouraged to develop independent projects in addition to supporting the research of the PI