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Research Fellow (Human-in-the-Loop AI perception system) (LX)

Job no: 498946
Department: Infocomm Technology
Contract type: Contract
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to deliver on an innovation research project where you will be part of the research team to conduct applied research in the topic of Human-in-the-Loop AI perception system that leverages user concerns and identified driving scenarios to generate new and relevant driving scenes for enhancing the perception system performance for autonomous vehicles (AV).

Key Responsibilities:

Participate in and manage the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables

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The Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU) in Odense invites applications for positions as Assistant, Associate, or Full professor in Health Informatics and Technology. The preferred start date is from January 2026 and the final start date will be agreed with the successful candidate(s).

SDU Health Informatics and Technology (HIT) strives to develop novel and ready to deploy technical solutions in a transdisciplinary manner. SDU HIT has a large portfolio of transdisciplinary projects involving numerous partners from healthcare, academia, industry and network organizations.

The Maersk Mc-Kinney Moller Institute is an internationally recognized research department with strong research units in robotics, drones, artificial intelligence, software engineering, energy informatics, and health informatics and technology.

Denmark is known to be a great place to live and work. There is a high quality of life in and around Odense, and at SDU we value a well-functioning work-life

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Job Description Summary

Auburn University’s National Center for Additive Manufacturing Excellence (NCAME) and the Department of Mechanical Engineering invite applications for an Assistant Research Professor. This position is a 12-month non-tenure track faculty assignment within the Auburn University research faculty family. This position will be responsible for conducting research and execute tasks specified in NCAME active projects. These include—but are not limited to—designing of experiments, microstructural/mechanical characterizations, and analysis, performing numerical simulations, advising undergraduate and graduate students, and writing reports, scholarly papers, and proposals. The selected individual will have a one-year written employment contract, which may be renewed for future years based on need, availability of funding, and performance. The total term of employment will not exceed the period of available funding from contract and grant, generated income, or other designated funds.

The National Center for Additive Manufacturing Excellence (NCAME) at Auburn University (AU), which was

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Neurodegenerative diseases like Alzheimer’s are a growing concern in the U.S., with over 7 million Americans living with Alzheimer’s disease today. By 2060, that number is expected to grow, affecting nearly 13 million people. These diseases are not only hard on individuals and families, but are costly, with more than $230 billion spent in the U.S. each year in caregiving alone. As the population ages, the need for new ways to detect and address the silent emergence of these diseases has never been more urgent. 

New artificial intelligence predictive models used in brain research may provide a way to better predict how a person’s brain ages over time, helping doctors recognize warning signs long before clinical symptoms surface. 

Supported by the U.S. National Science Foundation, a team of researchers led by Paul Bogdan, an associate professor in the University of Southern California Department of Electrical and Computer Engineering, has developed a cutting-edge AI system capable of generating a future MRI of a person’s brain from just a single scan. This technology opens the door to identifying subtle changes that may signal the earliest stages of neurodegenerative diseases — potentially years before traditional diagnostic methods could detect them.

To build the tool, the team combined two advanced AI techniques: a 3D diffusion model and a ControlNet, which allow the system to “control” or guide image generation

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