-
(including neural quantum states), stabilizer and near-Clifford simulation, Gaussian/free-fermion methods, open-system dynamics (Lindblad master equations). - Machine learning for physical systems: deep
-
seabed sensing research project focused on characterizing the upper-layer geoacoustic properties of deep-water seafloors. The position will support research involving acoustic sensing technologies, data
-
, or a related STEM field. Experience with EHR data, machine learning or deep learning, natural language processing, medical imaging, or large language models (LLMs) is highly desirable. Familiarity with
-
in our collections or on view in our galleries. We seek an individual with a passion for teaching and interdisciplinary thinking; a deep commitment to object-based learning and inquiry; and a
-
-of-the-art methods, datasets, and challenges Proven experience with: Video data processing for learning and inference Deep learning architectures for video analysis Python programming and PyTorch framework
-
University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 months ago
inventories) with satellite remote sensing data (e.g., spaceborne lidar and/or hyperspectral observations) and apply machine learning and deep learning approaches to address these questions. This position is
-
associate will work both independently and collaboratively to develop and apply novel deep learning algorithms and/or computational chemistry methods for small-molecule drug discovery targeting RNA
-
applications for a fully funded postdoctoral associate position. This position, available immediately, focuses on developing machine learning and deep learning methods for analyzing large-scale single-cell DNA
-
) mathematics, physics, or a related STEM fields. Strong programming and data analysis skills (e.g., Python, R) Solid understanding of machine learning, deep learning, and data modeling techniques Job Description
-
contributing to multiple projects including resilience-aware scheduling, deep learning workload job scheduling, and storage system performance tuning. The candidate will have the opportunity to engage in