Sort by
Refine Your Search
-
Listed
-
Category
-
Country
- United States
- United Kingdom
- Germany
- Netherlands
- Sweden
- France
- Norway
- Portugal
- Denmark
- Spain
- Belgium
- Poland
- Italy
- Singapore
- Ireland
- Hong Kong
- Romania
- Estonia
- Morocco
- Canada
- Israel
- Japan
- Lithuania
- Luxembourg
- Malta
- Vietnam
- Australia
- Austria
- China
- Cyprus
- Czech
- Europe
- Greece
- Switzerland
- United Arab Emirates
- 25 more »
- « less
-
Program
-
Field
-
or methodologies (e.g., drone infrastructure, networked sensors, AI-enabled control, and communication systems) into instructional and research setups, ensuring safety, reliability, and compatibility. Supports and
-
-Senftenberg (BTU) combines top-level research and knowledge transfer at an international level, thereby creating an interdisciplinary innovation network and an excellent hub for science and technology. Together
-
these areas and nurture future leaders in prosthetics and orthotics, clinical engineering, medical instrumentation and sensors, and biological engineering by imparting interdisciplinary knowledge, innovative
-
annual leave, plus 9 buildings closed days (and Christmas Eve when it falls on a weekday) for all full time staff. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards
-
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
-
Europe’s first doctoral network in digital endocrinology – integrating AI, sensor technology, omics, and clinical medicine to transform diagnosis and treatment of adrenal diseases. Digital medicine is
-
passionate about applying ML algorithms and developing AI applied research and innovation solutions using classic ML to novel transformer neural networks. We test and measure the real customer impact of each
-
materials, self-healing technologies, or sensor-integrated cementitious systems is a strong plus. Strong laboratory skills, data analysis capabilities, and a collaborative mindset. Preferred Skills
-
related fields Expert knowledge of building air-conditioning and mechanical ventilation, simulation, building automation and control, sensor network, thermal energy storage, indoor air quality, heat
-
for robotics, electrical and digital control systems, sensors and sensor networks within the Advanced Manufacturing specialisation through the UTAS Virtual Learning Environment (VLE) Foster student success and