Sort by
Refine Your Search
-
Listed
-
Country
-
Employer
- MOHAMMED VI POLYTECHNIC UNIVERSITY
- Chalmers University of Technology
- Harvard University
- McGill University
- National Aeronautics and Space Administration (NASA)
- Nature Careers
- Texas A&M AgriLife
- Texas A&M AgriLife Extension
- University of Chicago
- University of Maryland
- University of Nebraska Medical Center
- Vrije Universiteit Brussel
- 2 more »
- « less
-
Field
-
multimodal data (video, self-report, physiological sensors, automatic facial recognition software) that examines CER in multiple contrasting contexts. And (3) Advance educational theory and practice by
-
. To reach level-4/5 autonomy, we need teamwork: nearby vehicles, drones, and roadside units must co-perceive their environment, sharing and fusing complementary sensor views in real time. Yet raw video
-
data, including TPMS (Tire Pressure Monitoring System), high-speed wheel encoders, CAN (Controller Area Network) data, accelerometers, and acoustics data. Understanding of sensor technologies and their
-
is currently building and commissioning a network of calibrated multi-sensor observatory-class systems, and developing novel machine learning methods with the aim of collecting science-quality data
-
research program focuses on developing innovative cell-based therapies and model systems for CNS diseases, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, and brain cancers. We
-
and sustainable sensor systems for industrial applications. This position offers an exciting opportunity to contribute to cutting-edge research in the field of sustainable materials to develop promising
-
proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team
-
challenges and real-world impact. Project overview In recent years, generative neural network models for creation of photo-realistic images have become increasingly popular. Their training results in a low
-
experimentation, isotopic measurements and modeling aspects taking advantage of a network of international collaboration and collaborations with the private sector. Importantly, this project is associated to a
-
proficiency in languages such as R and Python. Experience in GIS, remote sensing, and processing projected climate data. Proven ability to manage multiple tasks effectively, work collaboratively in team