Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Field
-
appointment involves developing instrumental methods for enhancing proteins, especially plant proteins, functionalities and application in food products. Experience and willingness to learn Proteomics and/or
-
Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how
-
, United States of America [map ] Subject Area: Computational Science / Artificial Intelligence/Machine Learning Appl Deadline: (posted 2025/11/19, listed until 2026/01/26) Position Description: Apply Position Description
-
weak gravitational lensing, galaxy clusters, or large-scale structure. Experience with cosmological simulations and machine learning is highly desirable. Postdoctoral associate in exoplanet atmospheres
-
, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond. The particle physics phenomenology group members are: J. F. Kamenik (head), B. Bajc, S
-
, particularly radionuclides, on a continental scale. The aim is to develop a new class of inverse Bayesian models, STE-EU-SCALE, combining innovative forward dispersion models, machine learning techniques, and
-
affiliates reflect strengths in machine learning, biological modeling, data ethics, data sovereignty, computer science, environmental data science, climate change policy and modeling, evolutionary genetics
-
operations in the following areas: Soil & Groundwater; Deactivation & Decommissioning; Tank Waste; Robotics; Machine Learning; Artificial Intelligence; Cybersecurity; and Advanced Manufacturing. Are you
-
manufacturing. It is meritorious to have previous experience in data analysis and processing with Python (or similar), preferably including documented experience with machine learning tools. It is meritorious
-
research project Expertise in machine learning Additional expertise in one or more of the following: digital signal processing, statistics, multimodal processing, FAIR data management, music theory