Sort by
Refine Your Search
-
to one or several of the above topics. For more information on the research directions, applicants are encouraged to check Prof.Pierre Youssef’s research profile. The probability group at New York
-
generative AI models to establish structure-property relationships for materials discovery. This individual will be expected to collaborate closely with the project team and coordinate efforts with
-
communications Hardware-constrained signal processing for wireless communications Channel modeling and characterization Applications will be accepted immediately and candidates will be considered until
-
and causal inference (including virtual lab experiments); and/or (4) network or computational modeling. The ideal candidate will have a strong interest in applying these tools to questions of group
-
conjugation, neuroscience, and preclinical model experiments. The candidate will work in a dynamic, multidisciplinary environment alongside PhD-level engineers and scientists, graduate students, and full-time
-
the frontiers of developmental biology and disease modeling. The laboratory integrates stem-cell biology, fluorescence imaging, bioinformatics, and advanced nano- and micro-engineering to decode organogenesis and
-
, Neuroscience, or a related field. A strong background in functional neuroimaging with experience in decoding and/or encoding models is required. Candidates with experience with recurrent neural networks will be
-
networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic perspectives on large language models Statistical learning theory and complexity analysis
-
and metabolic disorders. These approaches entail device design and manufacturing, drug conjugation, neuroscience, and preclinical model experiments. The candidate will work in a dynamic
-
. We are seeking a Postdoctoral Researcher to join the team and make significant contributions to the field. The researcher is expected to have (i) strong machine learning skills to improve model