Associate Senior Lecturer in machine learning - Hiring in process/Finished, not possible to apply

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

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

Appointment as Associate Senior Lecturer is a qualifying appointment with the purpose to give the employee a possibility to promote to Senior Lecturer. Appointment as Associate Senior Lecturer is for four years.

Description
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.

Research will be carried out both independently and in collaboration with other members of the CAISR research group, across a variety of cutting-edge AI/ML topics, including representation learning, meta-learning transfer learning, multi-task, self-supervised and weakly-supervised learning, anomaly detection, and more. An example is jointly learning data representations that are useful for multiple tasks, allowing for autonomous adaptation to a specific task. From the application perspective, much of CAISR research concerns mobility data, which is often characterised by two crucially essential dimensions: spatial and temporal; 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. At the same time, vehicles generate raw sensor data that needs to be mapped into low-dimensional representations. The goal is to extract general features which are suitable for more than one task, often in self-supervised or semi-supervised setting. For example, for estimating the health state of different components, the representations that allow accurate predictions are related, but not necessarily the same, since those components can be related to different aspects of the vehicle operation.

Other directions of CAISR research include physics-informed machine learning, aware systems research and autonomous knowledge creation. AI and ML is also 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 data mining and machine learning research in one or several of the application domains where the university conducts research
• To contribute to academic publications and conference papers (where appropriate leading on these)
• To contribute to report writing

Qualification
- 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.
- Experience in teaching on advanced level in higher education.
- Pedagogical training in teaching in higher education.
- An Associate Senior Lecturer position requires that the doctoral degree was awarded within five years of the application deadline.

For appointment as an Associate Senior Lecturer, 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 master / PhD 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

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(Stefan.Byttner@hh.se).

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

Information for International Applicants
Choosing a career in a foreign country is a big step. Thus, to give you a general idea what we have to offer in terms of benefits and life in general for you and your family/spouse/partner please visit:
https://www.hh.se/english/about-the-university/vacant-positions/international-staff-support.html