Phd students WASP research program
Wallenberg Autonomous Systems and Software Program (WASP) is Sweden's largest individual engineering research program ever, and provides a platform for academic research and education on autonomous systems and software, see http://wasp-sweden.org
Lund University now offers up to two PhD positions within the following two research projects. In parallel, KTH, Linköping University, and Umeå University offer up to 6 PhD positions, i.e., up to 8 positions in total. You may apply to at most two of these 8 research projects. If you apply for two projects, you need to prioritize.
For general information about WASP at Lund University contact Karl-Erik Årzén (Phone: +46 (0)46 2228782, Email: email@example.com)
Projects for PhD studies
Project LU1: Efficient Learning of Dynamical Systems
The project aims to develop methods that learn complex dynamical models through algorithms that actively explore the behavior of the system. The key challenge is to trade the cost of “exploration” with the future benefits from the resulting improved knowledge. This area, sometimes named “dual control theory”, is now vitalized from recent progress in machine learning and statistical estimation. There is also an increased number of exciting applications where the problem is central, such as in self-driving vehicles and self-learning robots. The applicant should have an interest to work cross-disciplinary in the areas of control theory, signal processing, machine learning and statistics.
Project LU2: AI Reasoning for Situation Understanding in Human-Robot Interaction
When autonomous systems, or robots, interact with humans in an open-ended world (the real world), there will be situations where the system works according to its technical specifications, but its behaviour is incomprehensible for the user. The PhD project will thus investigate how a better situation understanding can be provided for systems that interact with humans in a mixed-initiative setting. Example problems include how such an interactive system can detect ambiguities in the user behaviour, how it can assess unexpected and ambiguous situations, and how suitable responses can be computed. Such responses can mean to act autonomously, or to ask the human for help to resolve an ambiguous situation. Machine learning and pattern classification techniques are assumed suitable for the identification of patterns in user behaviour, while the situation assessment and computation of appropriate actions and responses will be based on reasoning mechanisms, potentially including defeasible reasoning. Testbeds and opportunities for the demonstration of results include different mobile platforms, classic industrial manipulators, and collaborative robots available in the LTH Robot Lab, as well as the WASP demonstrator arena for Public Safety (WARA-PS).
Supervisor: Associate Professor Elin A. Topp, Department of Computer Science
Contact information: Phone: +46 (0)46 222 4249, Email: Elin_Anna.Topp@cs.lth.se
Additional information: http://cs.lth.se/Elin_Anna_Topp/phd-project
The main duties of doctoral students are to devote themselves to their research studies which includes participating in research projects and third cycle courses. The work duties will also include teaching and other departmental duties (no more than 20%).
A person meets the general admission requirements for third-cycle courses and study programmes if he or she:
has been awarded a second-cycle qualification, orhas satisfied the requirements for courses comprising at least 240 credits of which at least 60 credits were awarded in the second cycle, orhas acquired substantially equivalent knowledge in some other way in Sweden or abroad.Information about the specific admission requirements for the research subjects, please follow the link: http://www.lth.se/english/staff/teaching-and-research/phd-studies/study-...
Very good oral and written proficiency in English.The individual projects may have additional requirements. If so, these are provided among the additional information for the particular projects.Assessment criteria
Selection for third-cycle studies is based on the student's potential to profit from such studies. The assessment of potential is made primarily on the basis of academic results from the first and second cycle. Special attention is paid to the following:
Knowledge and skills relevant to the thesis project and the subject of study.An assessment of ability to work independently and to formulate and tackle research problems.Written and oral communication skills.Other experience relevant to the third-cycle studies, e.g. professional experience.Other assessment criteria:
The individual projects may have assessment criteria. If so, these are provided among the additional information for the particular projects.Consideration will also be given to good collaborative skills, drive and independence, and how the applicant, through his or her experience and skills, is deemed to have the abilities necessary for successfully completing the third cycle programme.
Terms of employment
Only those admitted to third cycle studies may be appointed to a doctoral studentship. Third cycle studies at LTH consist of full-time studies for 4 years. A doctoral studentship is a fixed-term employment of a maximum of 5 years (including 20% departmental duties). Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.
Instructions on how to apply
Applications shall be written in English and include a cover letter stating the reasons why you are interested in the position and in what way the research project corresponds to your interests and educational background. The application must also contain a CV, degree certificate or equivalent, and other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.).
If you apply for two projects, you need to prioritize.
The candidate should be able to start the PhD studies no later than January 1, 2018.
We will review the applications on a rolling basis, please submit your application as soon as possible.
- Karl-Erik Årzén, +46 (0)46 2228782, Mail: firstname.lastname@example.org
This job comes from a partnership with Science Magazine and