Sort by
Refine Your Search
-
, behavioral, and mindfulness-based treatments for anxiety; and modeling who benefits most from learning many emotion regulation skills or a single emotion regulation strength. The Post Doctoral Scholar will
-
studying deformation mechanisms in refractory alloys as via atomic-scale calculations as well as application of machine learning to materials discovery The ideal candidate will have the following
-
in brief cognitive, behavioral, and mindfulness-based treatments for anxiety; and modeling who benefits most from learning many emotion regulation skills or a single emotion regulation strength
-
of Biomedical Informatics (BMI) and the Pelotonia Institute for Immuno-Oncology (PIIO) are seeking a highly motivated Postdoctoral Scholar to work under the mentorship of Dr. Anjun Ma —a leader in deep learning
-
and improve communities locally and globally. We are seeking passionate individuals who are committed to making a meaningful impact through collaboration, innovation, and excellence. To learn more about
-
engineering or related fields. Candidates should have a strong research record in LLM-based agents, reinforcement learning, or large language models, preferably in areas closely aligned with the topics outlined
-
in Dr. Shanlin Ke’s lab. The overarching goal of Dr. Ke’s lab is to develop computational approaches and leveraging bioinformatics tools, metagenomic sequencing, multi-omics data, machine learning, and
-
machine learning—for chemical and biological applications. You will design and implement models ranging from molecular to process scales, develop model-predictive control and optimization strategies, run
-
data Experience with GIS/RS and database environments (e.g., ArcGIS and Quantum GIS) Experience with machine learning and statistical learning Experience working with large, diverse datasets Familiarity
-
decision-making for complex infrastructure systems. This position offers an opportunity to contribute to interdisciplinary research at the intersection of civil engineering, machine learning, and systems