185 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL"-"UCL" positions at Zintellect in United States
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Field
-
, machine learning, computer vision, and use of digital data collection strategies is preferred. Ability to communicate about strategies and tools implemented effectively to non-expert audiences. Ability
-
to clinical trials. Later, you will learn FDA’s Elsa, a large language model-powered AI tool for use in extracting and summarizing information from application files and labeling and develop new generative and
-
& Amputation Center of Excellence (EACE) is a unique organization within the Department of War (DoW) consisting of teams of researchers embedded at the point of care within multiple Military Treatment Facilities
-
research in several areas. These include, but are not limited to: Exploring machine learning techniques to analyze current systems and assess opportunities for improvement Gaining experience with virtual
-
of hydrate distributions and fluid migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter estimation tools and large
-
resolution visualizations of hydrate distributions and fluid migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter
-
for internal regulatory science databases. Additionally, you will have the opportunity to disseminate research findings to internal and external data stakeholders (e.g. publication) Learning Objectives: Under
-
and weaknesses for end-users. Help develop new or improve existing soil moisture estimates using NISAR and other datasets utilizing artificial intelligence (AI) and machine learning. The outcome from
-
to: Learning about aircraft systems engineering and systems analysis to support integrated design and performance assessment. Participating in aircraft design trade studies with a focus on propulsion–airframe
-
learn how phenotypic datasets are integrated with genomic data for association analyses, genomic selection, and AI-driven methods, including machine learning and deep learning, to enhance germplasm