Postdoctoral researcher in machine learning

at  Hgskolan i Halmstad

HALMSTAD UNIVERSITY

Work at a University where different perspectives meet!
Halmstad University adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, innovation and collaboration with society have characterised the University’s education and research. The research is internationally reputable and is largely conducted in a multidisciplinary manner within the University’s two focus areas: Health Innovation and Smart Cities and Communities. The University has a wide range of education with many popular study programmes. The campus is modern and well-equipped, and is situated close to both public transportation and the city center.
More information about working at Halmstad University: https://hh.se/english/about-the-university/vacant-positions.html

DESCRIPTION

Halmstad University aims to expand its strengths in machine learning (ML) and artificial intelligence (AI) as increasingly important drivers of society’s digitalization. Our partners can use AI/ML to tackle better challenges related to electromobility, and autonomous driving, as well as efficiency, reliability, and resilience of Industry 5.0.
The postdoc is expected to do research, both independently and in collaboration with other members of the CAISR research group, across various cutting-edge AI/ML topics, including data mining, context-aware systems, knowledge-based intelligent systems, representation learning, meta-learning, transfer learning, multi-task, self-supervised and weakly-supervised learning, federated learning, anomaly detection, synthetic data generation, graph neural networks, evaluation, verification and validation of intelligent systems, and more.
This is a two year position with a possibility to extension with one year if additional external funding is received.
The recruited person will have an opportunity to advance Bachelor and Master level courses such as Artificial Intelligence, Learning Systems, Data Mining, Applied Data Mining, and Deep Learning. The person will also be involved in the Graduate professional development program (second-cycle courses targeted at the business sector). The recruited person will be expected to teach up to 20% and do research at least 80%, within the project. Finally, the recruited person is expected to participate in supervision of thesis projects for bachelor and master level students, as well as co-supervise Ph.D. students.

QUALIFICATIONS

The applicant must hold a doctoral degree in Artificial Intelligence/Data Mining/Machine Learning/Information Technology or related fields. The applicant needs to demonstrate a strong research profile in the fields related to topics of interest for CAISR research environment, including recent activities with high impact. The scientific production is expected to be published in high-quality, peer-reviewed research journals and conferences. Documented experience from innovation, research and development in an industrial environment is also a strong merit. The applicant should share the value that diversity and equality among researchers and teachers brings higher quality to research and education.
Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position. The certificate, proving the qualification requirement is met, must be received before the employment decision is made. Primarily should those who have graduated no more than three years before the last application date, be considered. Under special circumstances, leave due to illness, parental leave, or similar circumstances, the doctoral degree can have been completed earlier.

For appointment as a postdoctoral researcher, the following assessment criteria will be applied:

• Ability to conduct research of high international quality in artificial intelligence, specifically data mining and machine learning
• Documented experience from research in collaboration with industrial partners and/or interdisciplinary teams
• Ability to conduct high-quality teaching and to develop courses at different levels
• Experience in supervision of bachelor/master students
• Ability to attract external funding
• Dynamism, curiosity, independence, creativity, and good teamwork
• Willingness to address opportunities and challenges within AI, machine learning and data mining

The duties will be:

• To perform research in the AI-MARiE project, related to online monitoring of complex and mixed equipment processes; especially in relation to work done by a fork-lift truck for material handling
• To contribute to academic publications and conference papers
• To contribute to report writing