Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Portugal
- Sweden
- France
- Germany
- Netherlands
- Spain
- Italy
- Singapore
- Norway
- Belgium
- Denmark
- Hong Kong
- Canada
- Japan
- Poland
- Australia
- Luxembourg
- Ireland
- Switzerland
- Lithuania
- United Arab Emirates
- Austria
- China
- Czech
- Morocco
- Estonia
- Malta
- Romania
- Saudi Arabia
- Brazil
- Cyprus
- Israel
- Slovakia
- Vietnam
- Croatia
- Europe
- Finland
- Greece
- Slovenia
- 31 more »
- « less
-
Program
-
Field
- Computer Science
- Engineering
- Medical Sciences
- Economics
- Science
- Biology
- Materials Science
- Mathematics
- Electrical Engineering
- Chemistry
- Earth Sciences
- Environment
- Business
- Education
- Humanities
- Linguistics
- Arts and Literature
- Psychology
- Social Sciences
- Sports and Recreation
- Physics
- Law
- Philosophy
- 13 more »
- « less
-
image analysis and sensor technologies (e.g. RGB/NIR) for textile production, as well as using machine learning for process optimisation and performance prediction from fibre to finished product
-
development to support extended reality technologies, machine learning pipeline integration, integration of sensors/devices to mobile platforms, and creating novel clinical decision support applications for our
-
position within a Research Infrastructure? No Offer Description About the job To lead the technical development, optimisation, validation, and field deployment of a smart optical nitrate sensor platform
-
of simulated sensors (vision, sonar, LiDAR, inertial navigation). - Implementation of guidance, control, and planning algorithms under environmental constraints. - Implementation of distributed simulation
-
associated molecules to functionally specialised units that either detect the pathogen (sensor NLRs) or execute the immune response (helper NLRs). Some sensor and helper NLRs work as genetically linked pairs
-
. Optimal sensor placement, identified through adjoint-based sensitivity analysis to improve assimilation efficiency. By embedding physical laws into data assimilation, these methods bridge the gap between
-
driven research team who are at the forefront of sensor technologies development and feedback process control for quality assurance tools and the next generation of renewable energy development. You will
-
an inclusive community of dedicated problem-solvers who hold themselves - and one another - to the highest academic and professional standards. To learn more about us, please visit https://seas.harvard.edu
-
of characteristic parameters for magnet protection as well as post-mortem quench data analysis. Experience in electrical measurement, sensor technology, analogue/digital signal processing and test data acquisition
-
smart electrical grid that increasingly relies on the use of intermittent renewable energy sources. Modern integrated building automation and control systems create an environment rich with sensor data