Description
Halmstad University, School of Information Technology
“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 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 computer science, computer engineering or
electrical engineering. Strong knowledge of machine learning is required
(especially meriting is skills and knowledge in deep learning) with methods
such as CNN, RNN, LSTM and Autoencoders. Programming skills in Python is
required, skills in other programming languages and software development
experience 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.
Type of employment Temporary position longer than 6 months
Contract type Full time
First day of employment 220701 or as soon as possible
Salary Monthly salary
Number of positions 1
Working hours 100%
City Halmstad
County Hallands län
Country Sweden
Reference number 2022/63
Contact
Stefan Byttner, +46729773601
Union representative
Kristina Hildebrand, Saco-S, 072-3734135
Anniqa Lagergren, OFR, 072-9773745
Camilla Soto, ST, 076-6087233
Published 04.May.2022
Last application date 17.May.2022 11:59 PM CEST
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