Doctoral student in machine learing - vehicle

“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 cross-border. Today, the University has around 600 employees and 12,000 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. The research is conducted within the research environment Embedded and Intelligent Systems (EIS). 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: http://www.hh.se/ite-en

More information about the research environment Embedded and Intelligent Systems: http://www.hh.se/eis-en

Description


The selected PhD student will carry out research on multi-task representation learning (i.e. jointly learning data representations that are useful for multiple tasks). This is an important topic as it allows for autonomous adaptation to a specific task, by learning features that are most appropriate.

From the application perspective, vehicles generate a large amount of raw sensor data that need to mapped into low-dimensional representation, as using the original raw data (e.g. for predictive maintenance) is not feasible. The overall goal is to extract general features which are suitable for more than one task, for example, estimating the health state of several different components. Since those components can be related to different aspects of the vehicle operation, the representations that allow accurate predictions are related, but not necessarily the same.

From the method perspective, a training setup is considered, in which not one, but rather multiple related tasks are provided. The PhD student will work on developing deep neural networks and methods for generating families of diverse representations from the set of training tasks. This is still a challenge, and most existing works rely on either supervised learning of a representation tailored towards a single task, or on unsupervised learning of a representation that captures general features but may not be well-suited to future tasks. The employment also includes teaching responsibilities corresponding to a maximum of 20% of full-time.

This is a full-time position available from September 1st 2021 (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. 

Qualifications
The ideal candidate has a Master’s degree in computer science, machine learning, robotics, mathematics, or a related engineering discipline. A strong background in machine learning, artificial intelligence, data mining, or signal processing is desirable. Excellent programming skills, analytical problem solving and organizational abilities are required. A good level of written and spoken English is required.

Students expecting to finalize their degree the coming month 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).

Salary
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.

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

3. copies of previous transcripts and degrees,

4. summary (1-2 pages) of the master’s thesis

5. a copy of previous publications and software samples, if any, and

6. 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.