Faculty of Engineering, LTH, Matematikcentrum, LTH

Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 42 000 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.

Position is available in the area of computer vision and machine learning, with applications to scene understanding (semantic segmentation, 3d reconstruction, object modeling, object and action recognition, and image categorization) from images and video sequences. This position is funded in part under the European Research Council Consolidator grant SEED. Funding is available for a period of up to 2 years.

The research aims to design generally applicable methods for visual feature extraction based on hierarchical (deep) architectures as well as large-scale numerical optimization and machine learning techniques with a general demonstrator emphasis towards dynamic scene understanding -- relational models of visual scenes containing people interacting with objects.

Depending on the interest and strengths of the candidate the work can focus on one (or several) of the following aspects: numerical optimization and machine learning algorithms including deep learning and reinforcement learning, 2d or 3d modeling, hierarchical feature extraction, computational visual attention mechanisms, semantic segmentation, object recognition and image categorization.

The approach is strongly research oriented, targeting contributions to be published in high-profile international journals and conferences in computer vision, machine learning and computer graphics. We focus on novel theoretical and algorithmic contributions, but also the design of associated proof-of-concept prototypes.

Subject
Mathematics with focus on Computer Vision and Machine Learning

Work duties
The main duties involved in a post-doctoral posistion is to conduct research. Teaching may also be included, but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning.

Detailed description of the work duties, such as:

  • Research within the subject area. The successful candidates will be involved in research along one of the above themes in collaboration with Prof. Cristian Sminchisescu and his group members.
  • Development of proof-of-concept prototypes

Based on the interest of the candidate there would be opportunities for teaching, supervision of degree projects and doctoral student, as well as participation in externally research funded projects.

  • Collaboration with industry and wider society
  • Administration related to the work duties listed above

Qualification requirements
Appointment to a post-doctoral position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier.

Additional requirements:

  • Very good oral and written proficiency in English.
  • Strong mathematical background, familiarity with scientific programming environments (Matlab, TensorFlow, Caffee) as well as programming languages C/C++/Python.
  • The applicant should have in addition to a PhD degree at least one publication at a major computer vision or machine learning top-level international conference of journal including ICCV, CVPR, ECCV, ICLR, ICML, NIPS, PAMI, IJCV, JMLR.

Assessment criteria and other qualifications
This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers.

Particular emphasis will be placed on research skills within the subject.

For appointments to a post-doctoral position, the following shall form the assessment criteria:

  • A good ability to develop and conduct high quality research.
  • Publications in high-profile journals and conferences including ICCV, CVPR, ECCV, ICLR, ICML, NIPS, PAMI, IJCV, JMLR.
  • Oral communication and presentation skills.

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant’s experience and skills complement and strengthen ongoing research within the department, and how they stand to contribute to its future development.

Terms of employment
This is a full-time, fixed-term employment of a maximum of 2 years. The period of employment is determined in accordance with the agreement “Avtal om tidsbegränsad anställning som postdoktor” (“Agreement on fixed-term employment as a post-doctoral fellow”) between Lund University, SACO-S, OFR/S and SEKO, dated 4 September 2008.

Instructions on how to apply
Applications shall be written in English. Please draw up the application in accordance with LTH’s Academic qualifications portfolio – see link below. Upload the application as PDF-files in the recruitment system. Read more:
http://www.lth.se/index.php?id=71223

Type of employment Temporary position longer than 6 months
Contract type Full time
First day of employment As soon as possible
Salary Månadslön
Number of positions 1
Working hours 100 %
City Lund
County Skåne län
Country Sweden
Reference number PA2017/3341
Contact
  • Professor Cristian Sminchisescu, 046-2223498
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62, st@st.lu.se
  • SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64, kansli@saco-s.lu.se
  • SEKO: Seko Civil, 046-222 93 66, sekocivil@seko.lu.se
Published 31.Oct.2017
Last application date 21.Nov.2017 11:59 PM CET

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