Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Program
-
Field
- Computer Science
- Engineering
- Biology
- Medical Sciences
- Science
- Economics
- Earth Sciences
- Materials Science
- Business
- Mathematics
- Chemistry
- Electrical Engineering
- Linguistics
- Arts and Literature
- Environment
- Physics
- Psychology
- Law
- Education
- Humanities
- Philosophy
- Social Sciences
- Sports and Recreation
- 13 more »
- « less
-
., probability, analysis), eager to conduct cutting edge research in the field of uncertainty quantification, in particular the theory and methods known as predictive Bayes. Predictive Bayes theory involves
-
Optimization (AI/ML) Developing AI/ML models to predict drillability issues based on mechanical rock properties Real-time parameter optimization (WOB, RPM, flow rate, etc.) using machine learning techniques
-
polygenic risk scores, rare variant burden scores, and integrative prediction models. Evaluate model performance and clinical utility. Identify therapeutic targets and causal risk factors for cardiovascular
-
project working to develop real-time vector-borne disease risk assessment in low resource areas. The individual will be directly responsible for the development of adaptive predictive models for nowcasting
-
trends and composition analysis, refractive index determination, and morphology for applications such as environmental monitoring, nuclear non-proliferation, and improving predictive modeling tools (e.g
-
injury risk analysis, predictive analytics, and recruitment and talent identification models; Works with individual players and helps them develop on the field through video analysis; Participates in
-
smoking and tobacco use at all of its university-controlled properties. The UC San Diego Annual Security & Fire Safety Report is available online at: https://www.police.ucsd.edu/docs/annualclery.pdf
-
, product management work, and and leadership responsibilities • Familiarity with artificial intelligence and machine learning approaches, including predictive modeling and precision analytics applied
-
broader portfolio of academic affairs and data science initiatives, including AI integration, predictive modeling, statistical analysis, machine learning, and analytics infrastructure development. A major
-
they change through time. To translate eBird observations into robust data products we create custom modeling workflows designed to fill spatiotemporal gaps based on remote sensing data while controlling