Postdoctoral researcher in machine learning

“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 adds value, drives innovation and prepares people and society for the future. Since the beginning in 1983, the University has been characterised as forward-thinking and collaborative. Halmstad University offers popular and reality-based education programmes. The research is profiled within two focus areas: Health Innovation and Smart Cities and Communities. 

The research at Halmstad University is internationally renowned and is pursued in multidisciplinary innovation and research programs. The University takes an active part in the development of society through extensive and recognised collaboration with both the private and 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: hh.se/ite-en

Description
This is a two year position with a possiblity to extension with one year if additional external funding is received.

The recruited person will be expected to teach up to 20% and do research at least 80%, within one orseveral 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 machine learning 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.

Principal duties
The duties will be:

• To undertake machine learning research and application development within the project
• To contribute to academic publications and conference papers (where appropriate leading on these)
• To contribute to report writing

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 this position, 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 ago before last application date, be considered.

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 machine learning
• Ability to conduct research independently
• 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 master / PhD students
• Ability to attract external funding
• Dynamism, curiosity, independence, creativity and good teamwork
• Willingness to address opportunities and challenges within AI and machine learning

Salary
Salary is to be settled by negotiation. The application should include a statement of the salary level required by the candidate.

Application
Applications should be sent via Halmstad University's recruitment system Varbi (see link on this page).

How to design your application

For further information, please contact Stefan Byttner([email protected]) or head of school Magnus Clarin ([email protected]).

General Information
We value the qualities that gender balance and diversity bring to our organization. We therefore welcome applicants with different backgrounds, gender, functionality and, not least, life experience.
Read more about Halmstad University at http://hh.se/english/discover/discoverhalmstaduniversity.9285.html