Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- University of Oslo
- University of Bergen
- NTNU - Norwegian University of Science and Technology
- University of South-Eastern Norway
- Western Norway University of Applied Sciences
- UiT The Arctic University of Norway
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- Nature Careers
- UNIS
- University of Agder
- University of Stavanger
- Østfold University College
- 2 more »
- « less
-
Field
-
thermal imaging data, and potential clinical and signal data, to create algorithms capable of recognizing key clinical activities and interventions. Building on recent advances in computer vision and
-
gauges, solenoid valves, resistive heaters and thermocouple sensors, PID controllers, actuated gate valves, etc. Programming in LabView environment for real-time instrument control. Implementation of a
-
patterns Multi-sensor fusion and adaptive threat assessment AI-driven decision support for maritime situational awareness The research will be aligned with three major European projects—SMAUG, SEAGUARD, and
-
collaboration in optimising data analysis algorithms for the raw detector data, including improving position reconstruction and pulse-shape discrimination algorithms which can be implemented on in the front-end
-
at Centre for Space Sensors and Systems (CENSSS) at the Department of Technology Systems (ITS). Starting date no later than November 1, 2025. The fellowship period is three years. A fourth year maybe
-
properties. The direct integration of such nanomaterials in microelectronic chips / CMOS can enable fabrication of compact, wireless, power-efficient, low-cost smart sensors (e.g., gas and pressure). In this
-
information of the data to make a prediction using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms
-
develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address major challenges in important applications including marine domain and
-
mathematical modelling tools. Excellent knowledge of programming languages such as R, Python, Julia, etc. Familiarity with AI algorithms and Machine Learning Fluent oral and written communication skills in
-
will be part of the project group ''Cancer Biology in Silico '' led by Chloé B. Steen, with strong collaborations with researchers at Oslo University Hospital, University of Oslo, and Stanford University