Doctoral student in machine learning - Halmstad University, School of information Technology - Administratörsjobb (offentlig verksamhet) i Halmstad
Doctoral student in machine learning
Halmstad University, School of information Technology / Administratörsjobb (offentlig verksamhet) / Halmstad
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Recent growth in the research activities and the well-established educational programs at the School of Information Technology (ITE) at Halmstad University is enabling a significant expansion.

In 2018, the total research expenditures where over 70MSEK and the number of students exceeded 850. Center for Applied Intelligent Systems Research at Halmstad University announces the availability of a fully-funded Ph.D. position in Computer Science and Engineering.


The selected Ph.D. student will carry out research to develop general lifetime models for all vital components in the electrical driveline of heavy duty vehicles. Hybrid and fully electric buses must take advantage of predictive maintenance services based on Machine Learning in order to remain competitive in the market despite their increased cost. Those new technical solutions are enabled by the possibility of collecting more precise and extensive data. Motivating example is the main battery, a component that is responsible for large fraction of the vehicle cost, and is expected to survive over 10 years. In the project we will create a data-driven model for battery health degradation, based on Transfer Learning paradigm utilising recent advancements in the field of deep learning, namely Generative Adversarial Networks. Historical data on failures of electric driveline components is not available due to its technological novelty, thus the right support for drivers, fleet operators and OEMs requires studies and development of new ML techniques. The goal is to enable predictive and prescriptive maintenance solutions that are capable of adapting to rapid changes in technology and continuous arrival of new observational data. This must be bootstrapped by leveraging available expert knowledge in the form of adaptive models for the evolving technology through AI solutions.

The research will be performed within the EVE (Extending life of Vehicles within Electromobility era) project in close collaboration with Volvo Buses and Volvo Group Connected Solutions. Therefore, the candidate will be spending time both at Halmstad University and at Volvo premises in Gothenburg. The employment also includes teaching responsibilities corresponding to a maximum of 20% of full-time. Applicant will be part of an international research group and an English-speaking environment.

This is a full-time position available from June 2019 (or as soon as possible afterwards) for a period of four years (extended one year at a time, subject to satisfactory progress of the Ph.D. study). Enough resources to fund experiments and conference travels are available.


The ideal candidate has a Master's degree in computer science, machine learning, data science, robotics, mathematics, physics, or a related engineering discipline. A strong background in machine learning, or data mining is desirable. Excellent programming skills, analytical problem solving and organizational abilities are required. Prior practical experience in deep learning is a plus.

Students expecting to finalize their degree during the spring 2019 are also welcome to apply. Only persons who are being admitted, or already have been admitted, to doctoral studies at an institution of higher education may be appointed doctoral students. (The Higher Education Ordinance Chapter 5, § 3). The student's ability to benefit from doctoral studies will be taken into account when we make the appointment. (The Higher Education Ordinance Chapter 5, § 5).


Doctoral students are employees of the University and paid a salary according to a uniform salary scale, adjusted in relation to the progress in education.

The position includes studies up to a doctoral degree and is annually extended in accordance with the Higher Education Ordinance Chapter 5, §7. The total employment period is four years but may be extended to a maximum of five years if the student performs 20% teaching or other tasks within the university.


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

1. a cover letter stating the purpose of the application and a brief statement of why you believe that your background and goals are well-matched with the goals of this position,

2. a Curriculum Vitae that includes at least

a. a list of previous degrees, dates, and institution, transcripts for higher-education studies until most recent available

b. a complete list of publications and a description of previous research and other work experience and links to online copies of the most important publications

3. copies of previous transcripts and degrees,

4. a copy of previous publications, if any, and

5. contact information for three reference persons.

List of qualifications and other documents that the applicant wishes to refer to should be enclosed with the application. All copies must be attested.

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.
The working language at Halmstad University is English and knowledge of the Swedish language not required to start working. Also for daily life, English is spoken widely and Sweden has the highest English Proficiency index in the world. Learning to speak Swedish will make it easier to interact with public and private services, to follow local and national issues, to participate in teaching junior students, and to participate in administrative and leadership roles. National Swedish language courses (SFI) are
available on campus. Read more about Halmstad University at

Varaktighet, arbetstid
100%. Tillträde: 2019-06-01 or as soon as possible Visstidsanställning


Monthly salary

Så ansöker du
Sista dag att ansöka är 2019-05-17
Ange följande referens när du ansöker: 2019/44
Klicka på denna länk för att göra din ansökan

Stefan Byttner 035-167792
Håkan Pettersson 035-167306

Halmstad University, School of Information Technology

Halmstad University, School of Information Technology
Kristian IV:s väg 3
30118 Halmstad

Kristian IV:s väg 3


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