Lund University, LTH,

Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 40 000 students and 7 400 staff based in Lund, Helsingborg and Malmö. We are united in our efforts to understand, explain and improve our world and the human condition.

LTH forms the Faculty of Engineering at Lund University, with approximately 9 000 students. The research carried out at LTH is of a high international standard and we are continuously developing our teaching methods and adapting our courses to current needs.

Machine learning is the discipline concerned with computer software that can learn autonomously. Machine learning, including both neural network-based approaches and mathematical statistics-based approaches, has become a driving force behind many recent breakthroughs in artificial intelligence. From speech recognition, image analysis, natural language understanding, machine translation, query and answering systems, protein folding, and even playing GO, machine learning is breaking records. These exciting developments have not gone unnoticed to industry either: Google, Facebook, IBM, Qualcomm, Yahoo, Microsoft, Bosch, Uber and so on all have large teams of researchers working with machine learning.

Subject description
Machine learning is a broad subject with connections to several departments at Lund University. For this reason, we therefore state four different subject directions, coupled to the four departments participating in the call. The final departmental affiliation will be decided in connection to the employment.

  1. Machine learning for control. This direction is mainly concerned with theory and methodology for the use of machine learning in dynamic feedback systems. Examples of this are reinforcement learning and deep reinforcement learning. Also the use of control methodology, such as dynamic programming and optimization, for improved machine learning efficiency is of interest.
  2. Machine learning in computer science with focus on theory, methodology, and programming tools for applications of machine learning for natural language processing, medicine, or new directions for knowledge management in robotics and software engineering.
  3. Machine learning in the mathematical sciences (including pure mathematics, applied mathematics, mathematical statistics and numerical analysis). This direction will focus on theoretical aspects of machine learning, such as limitations of machine learning, learning techniques under qualitative restrictions and dynamic optimisation techniques for high-dimensional non-stationary signals and also applications within image analysis and signal processing.
  4. Machine learning within electrical and information technology. This direction is oriented towards signal processing and implementation and is focusing on machine learning for communication, identification and positioning. It is also of interest to include aspects arising with resource constrained devices in terms of limited memory, processing or battery capabilities.

Work duties
Employment as an associate senior lecturer is a career development position and  aims for the holder to develop his or her independence as a researcher and educator. The work duties mainly involve research and teaching including supervision at undergraduate, graduate and doctoral levels. Included in the duties is also to actively participate in and to develop contacts with external funders, within academia as well as outside, and to contribute in efforts to attract external funding. The position shall include the opportunity for five weeks of training in higher education teaching and learning.

Qualification requirements

Appointment to associate senior lecturer requires that the applicant has

  • a PhD degree or acquired corresponding research expertise.

Priority should be given to applicants who have completed their degree or acquired the corresponding expertise no more than five years before the expiration date of the call.

Additional requirements:

  • Very good oral and written proficiency in English.

Assessment criteria
For appointments to associate senior lecturer, the following shall form the assessment criteria:

  • research excellence proved by scientific publications.
  • international research experience and potential to strengthen the research area within Sverige
  • pedagogical skills and insights regarding state-of-the-art pedagogics in the field

Other qualifications:

  • interest in and insights regarding academic leadership as well as interaction with the surrounding society
  • administrative skills as well as other skills

Consideration will also be given to how the applicant’s experience and skills complement and strengthen ongoing research, education and innovation within the department, and potential to contribute to its future development.

Terms of employmentThis is a full-time, fixed-term employment of  4  years. The period of employment is determined in accordance with Chapter 4 Section 12a§ HEA.

Instructions on how to apply
Applications shall be written in English. Draw up the application in accordance with the Academic qualifications portfolio at LTH, se link below, and attach it as three PDF files (in the recruitment system). Read more here:

http://www.lth.se/index.php?id=71223

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Promotion to senior lecturer in Machine Learning

During the period of employment, an associate senior lecturer can apply for appointment to a permanent position as senior lecturer if he or she has the required qualifications listed below, and is deemed to be suitable. 

Qualification requirements:
Appointment to senior lecturer requires that the applicant has:

  • A PhD or corresponding research competence or professional expertise considered important with regard to the subject matter of the post and the work duties it will involve.
  • Demonstrated teaching expertise.
  • Completed five weeks of training in higher education teaching and learning, or acquired equivalent knowledge by other means.

Additional requirements:

  • Very good oral and written proficiency in English.
  • Good ability to cooperate. Independence and drive.

Assessment criteria:

  • When assessing the applicants, special importance will be given to research and teaching expertise.
  • For appointments to senior lecturer, the following shall form the assessment criteria:
  • A good national and international standing as a researcher. The requirement for international experience shall be assessed with consideration to the character and traditions of the subject.
  • Good teaching ability, including a good ability to conduct, develop and lead teaching and other educational activities on different levels and using a variety of teaching methods.
  • An ability to supervise doctoral students to achieve a PhD.
  • An ability to collaborate with wider society and communicate his or her activities.
  • A good general ability to lead and develop activities.
Type of employment Permanent position
Contract type Full time
First day of employment As soon as possible
Salary Monthly
Number of positions 1
Working hours 100 %
City Lund
County Skåne län
Country Sweden
Reference number PA2018/2161
Contact
  • Daniel Sjöberg, +46 (0)462227511
Union representative
  • SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64, kansli@saco-s.lu.se
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62, st@st.lu.se
Published 12.Jun.2018
Last application date 12.Aug.2018 11:59 PM CET

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