Vacancies – AI Lab
Vacancies
Associate Professor in Artificial Intelligence (AI) and Health
At the Department of Public Health and Nursing (ISM) there is a vacancy for a tenure-track position as part of the Onsager Fellowship Programme.
The Onsager Fellowship programme at NTNU is designed to attract talented early-career scholars with a track-record of high quality published research, ready to work independently and with the potential to become a research leader. The tenure-track associate professor’s duties will primarily include research, but also include supervision, teaching, and other duties necessary to qualify for a permanent professor position within 6-7 years. Employment will be at the Department of Public Health and Nursing, anchored in the Musculoskeletal Research Group, and connected to the Norwegian Open AI Lab (NAIL) and the Data and Artificial Intelligence (DART) unit at the Department of Computer Science.
Read more about the position and apply through Jobbnorge.
Application deadline: February 1 2023
Postdoctoral Fellow in the use of AI in Employee Recruitment
At the Department of Computer Science (IDI) there is a vacancy for a postdoctoral fellow in the Data and Artificial Intelligence Group (DART), the use of AI in the recruitment process, with a special focus on fairness in decision making.
The position is funded by NTNU and will partly be connected to a project focusing on bias, discrimination and unfairness problems related to the use of AI in the employee recruitment process. The project (with short title “BIAS”) is funded by the European Union (EU) and is of highly multidisciplinary nature where the task of our department focuses on design and implementation of an AI-based decision support system that enables detection of possible unfair decisions, and development of methods to mitigate or avoid unfair decision.
In the BIAS project real data on job applications will be used. The postdoc researcher will work with data curation and the design and implementation of an AI-based decision support system, in particular for scanning and ranking the applications. A key requirement of the decision support systems is fairness, more specifically individual fairness where methods for measuring similarity between job applications will be of special focus.
Read more about the position and apply through Jobbnorge.
Application deadline: February 26 2023
PhD Candidates in the Field of Unconventional Computing in Nanomagnet Substrates
At the Department of Computer Science (IDI) there is a vacancy for up to two
PhD Candidates in the Field of Unconventional Computing in Nanomagnet Substrates.
The research group is seeking radical breakthroughs for unconventional computing exploring spin-based device technologies (Artificial Spin Ice (ASI)). One of their research visions is to use artificial spin systems as a platform for efficient and powerful data analysis at all scales, ranging from low power computation in the simplest sensor node to accelerated data processing in the most complex supercomputer. They are currently looking for PhD candidates to explore the computational possibilities in 2D artificial spin systems and explore the case for such systems to be harnessed for data processing.
These positions are part of the SPrINTER project funded by the Research Council of Norway and NTNU. In the SPrINTER project, experts in the fields of nanotechnology and computer science join forces to create a radically new technology for low-power wireless devices that do not require batteries to operate. They propose a technology built on the unique properties of nanomagnets to achieve their ambitious goal.
Read more about the position and apply through Jobbnorge.
Application deadline: February 13 2023
PhD Candidate within Artificial Intelligence for Anomaly Detection
At the Department of Computer Science (IDI) there is a vacancy for a PhD Candidate within Artificial Intelligence for Anomaly Detection. The position is connected with the SFI NorwAI.
Wireless embedded sensor nodes can perform increasingly complex inference tasks directly on the device. This makes such devices suitable for instrumenting a large number of machines, equipment or other items with the goal to detect anomalies in their operation. The problem remains to learn what constitutes anomalies that should be reported and distinguish them from normal changes in operation or variations between devices. Together with partners in the NorwAI SFI, the candidate will work on methods and prototypes to detect and classify anomalies, study transfer learning between devices, and explore how expert knowledge can be considered in the specific setting of distributed and streaming sensor data.
Read more about the position and apply through Jobbnorge.
Application deadline: February 27 2023