Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- Singapore
- France
- United Kingdom
- Portugal
- Norway
- Netherlands
- Germany
- Italy
- Spain
- Sweden
- Poland
- Belgium
- United Arab Emirates
- Australia
- Canada
- Austria
- Denmark
- Japan
- Luxembourg
- Switzerland
- Greece
- Hong Kong
- China
- Finland
- Mexico
- Brazil
- Czech
- Estonia
- India
- Romania
- Saudi Arabia
- Slovenia
- Bulgaria
- Croatia
- Cyprus
- Europe
- Ireland
- Morocco
- New Zealand
- 30 more »
- « less
-
Program
-
Field
-
Communication sciences Information science Engineering » Communication engineering Engineering » Electronic engineering Mathematics » Applied mathematics Mathematics » Probability theory Mathematics » Algorithms
-
University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 22 hours ago
-processing and machine-learning algorithms that account for skin pigmentation, low perfusion, and motion. Work with UNC clinical collaborators on IRB-approved human-subjects validation studies, including
-
Strong skills in simulation methodologies Excellent communication and interpersonal skills Desirable Criteria: Familiarity with machine learning algorithms and artificial intelligence as applied
-
Systems Lab (https://psl-ntu.github.io ) at NTU’s CCDS. The role focuses on designing, developing, and evaluating efficient, scalable systems for modern multi-agent HPC-AI workflows. Responsibilities
-
assignment of a research grant, with 1 position(s), under the project with the title “Multiple neighbourhood exploration in combinatorial optimisation”. Where to apply Website https://www.apply.uc.pt
-
teaching scenarios both supported on an existing Hardware-in-the-Loop (HIL) equipment, enabling students to deploy their own control algorithms, state eObjectives By the end of the three-month period, the
-
central role in supporting research design, algorithmic development, data analysis, and coding tasks across CTED’s interdisciplinary projects. Working under the direction of the Principal Investigator (PI
-
) imaging instruments and quantitative calibration protocols. Optimization of μXRF data acquisition protocols to maximize signal complementarity. Participate in the development of algorithms to optimize HMSPL
-
following fields (preferably several): recommender systems, user modeling, algorithmic fairness and ecological aspects (e.g., of recommendation algorithms/systems), simulation studies (e.g., simulation
-
the human musculoskeletal system, or experience providing engineering, hardware, statistical, or algorithmic support for such research (e.g., in biomechanics, biomedical signal processing, analysis of data