Research Engineer

“Our School and research environment is in a very exciting and expansive phase.

It is a large research environment with a strong international character. The goal is to be a nationally leading environment within, among other things, applied AI” – Magnus Clarin, Dean of the School of Information Technology.

Halmstad University
Halmstad University prepares people for the future by creating values, driving innovation and developing society. Since the beginning in 1983, the University has been characterised as forward-thinking and cross-border. Today, the University has around 600 employees and 11,000 students. The range of education is wide and the research is internationally renowned. Halmstad University actively participates in social development through collaboration with both industry and the public sector. More information about working at Halmstad University: https://hh.se/english/about-the-university/vacant-positions.html


The School of Information Technology
Halmstad University consists of four interdisciplinary Schools and the current position is located at the School of Information Technology (ITE). ITE is a multicultural school with around 130 employees from 20 different countries. It is a strong research and education environment, with focus on smart technology and its applications. Students and researchers are working with everything from AI and information driven care to autonomous vehicles, social robotics and digital design. ITE offers education on all levels, from undergraduate to PhD education, plus education for professional. Research is conducted within aware intelligent systems, smart electronic systems, cyber physical systems and digital service innovation. These four areas constitute the four technology areas of ITE. An innovation centre for information driven care called Leap for Life is connected to ITE, as well as a collaboration arena for electronic development, Electronics Centre in Halmstad (ECH).

More information about the School of Information Technology: https://hh.varbi.com/center/tool/position/390021/edit/tab:1/hh.se/ite-en


Description
This position is a one year postion and requires a combination of many different skills.

The recruited person will be expected to teach up to 20% and do research at least 80%, within one or several scientific projects. Research activities will depend on competences and interests, but are expected to build upon our existing portfolio.

The FREEDOM project analyses mobility data, as characterised by two crucially essential dimensions: spatial and temporal. From a technical perspective, obtaining a complete picture requires a framework capable of modelling them simultaneously to take advantage of the insights embedded in the interrelations between the two. Graph Neural Networks (GNNs) is an emerging and promising field of machine learning, in the intersection of deep neural networks and graph theory, that is uniquely suitable to address both aspects.

In the XPM project, we aim to develop several different types of explanations for predictive maintenance (anything from visual analytics through prototypical examples to deductive argumentative systems) and demonstrate their usefulness in four selected case studies: electric vehicles, metro trains, steel plant and wind farms. In each of them, we will demonstrate how the right explanations of decisions made by AI systems lead to better results across several dimensions, including identifying the component or part of the process where the problem has occurred; understanding the severity and future consequences of detected deviations; choosing the optimal repair and maintenance plan from several alternatives created based on different priorities; and understanding the reasons why the problem has occurred in the first place as a way to improve system design for the future. The key technical direction is physics-informed machine learning.

AI and ML is an important part of our education. 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). Finally, the recruited person is expected to participate in supervision of thesis projects for bachelor and master level students.

Qualifications
- M.S. degree or equivalent in Engineering, Computer Science/Information Technology or realted fields.
- Strong interest and research experience in the fields related to topics of interest for CAISR research environment, including recent research activities with high impact.
- Documented experience from innovation, research and development in an industrial environment is also a strong merit.
- Experience in teaching is a plus.

For appointment as a research engineer, 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 on industrially relevant projects, possibly 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 master students and/or international collaboration
- 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

General Information:
We value the qualities that gender balance and diversity bring to our organisation. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.