Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- University of Oslo
- Carnegie Mellon University
- Nanyang Technological University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- ;
- Barcelona Beta Brain Research Center
- Barnard College
- FCiências.ID
- Florida Atlantic University
- Harvard University
- INESC TEC
- Instituto Superior Técnico
- NTNU Norwegian University of Science and Technology
- National University of Singapore
- New York University
- OsloMet
- UiT The Arctic University of Norway
- University of Michigan
- 8 more »
- « less
-
Field
-
reliably in challenging environments (e.g., low texture, illumination variation, dynamic scenes, or sensor degradation). The research will integrate model-based estimation methods (e.g., filtering, factor
-
on an innovation research project where you will be part of the research team to conduct applied research in the topic of Human-in-the-Loop AI perception system that leverages user concerns and identified driving
-
focused on biodiversity, societal transformation and just environmental futures. You will contribute to mixed method research that maps public perceptions, emotional and structural barriers to environmental
-
perception models used in robotic safety loops. Research on runtime assurance, uncertainty monitoring, and evaluation metrics for safe human-aware robot operation. A combination of education and relevant
-
. Long-horizon and safety-aware planning under uncertainty. Function 2 2. Learning-Based Perception and Control Multi-modal and foundation-model-based approaches for robotics, including: Multi-modal
-
perception models used in robotic safety loops. Research on runtime assurance, uncertainty monitoring, and evaluation metrics for safe human-aware robot operation. A combination of education and relevant
-
of the following areas: robotics, machine learning, robot perception, underwater systems, nonlinear control, system modelling, or autonomous manipulation Strong programming skills and a solid
-
, the fellow must:; 1. Define a conceptual model of HCAI, identifying entities (human, system, decision, feedback) and their relationships; 2. Represent the model using diagrams, a lightweight ontology, or
-
to conduct applied research in the topic of Human-in-the-Loop AI perception system that leverages user concerns and identified driving scenarios to generate new and relevant driving scenes for enhancing
-
resulting agricultural greenhouse gas emission trajectories, shaped by producer behaviour; 3) Engage with modelling community and livestock producers aimed at improving the representation of livestock systems