Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- France
- Germany
- United Kingdom
- Belgium
- Portugal
- Sweden
- United Arab Emirates
- Luxembourg
- Netherlands
- Norway
- Australia
- Singapore
- Spain
- Poland
- China
- Canada
- Hong Kong
- Romania
- Switzerland
- Austria
- Denmark
- Ireland
- Italy
- Japan
- Vietnam
- Andorra
- Brazil
- Czech
- Finland
- India
- Israel
- Morocco
- Saudi Arabia
- Slovenia
- 25 more »
- « less
-
Program
-
Field
-
interactive learning objects and activities Create accessible charts/graphs/diagrams Create animations, animated movies and 3D models Communicate regularly with team members, Team Lead, and Project Coordinator
-
and Sobolev-type spaces (with Hytönen and/or Korte), Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic game
-
, and clinical safety datasets Implement graph-based retrieval-augmented generation (RAG) methods to enhance knowledge extraction and information synthesis Develop cross-pathway analytical methods using
-
graphs on research data Assist with site inspections and field oversight May have supervisory responsibilities Other duties as assigned Unit URL https://www.uidaho.edu/sci/biology Position Qualifications
-
responsibilities. Experience Essential: E1 Experience of analysing human body movement from sensor data (eg RGB videos and/or MOCAP data) using Deep Neural Networks (such as Graph Convolutional Networks). E2
-
25,000 students are enrolled in graduate course work, studying in disciplines ranging from atomic physics and graph theory to medieval literature and blind rehabilitation. Of 101 graduate offerings
-
/ Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date machine learning libraries Excellent written and verbal communication skills Track record of publishing
-
, Optimization, and AI • ML/AI for mobility prediction and optimization • Graph algorithms, network science • Spatiotemporal modeling • Operational research for mobility and infrastructure • Real-World Practice
-
. demonstrated research capability in one or more of the following areas: quantitative modelling of dynamic or adaptive systems reinforcement learning, multi-agent systems, network or graph-based models simulation
-
knowledge graphs, rules, and process understanding, with implications across sectors from ecology to infrastructure. 4. Theme 4 (“Communities”): Green and Resilient Communities and Entrepreneurship