Lunds universitet, Lunds Tekniska Högskola, Matematikcentrum, 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 7 600 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.

Project description
This position is part of a collaboration between Mathematical Statistics and the department of Physical Geography and Ecosystem Science, both at Lund University. The aim of the collaboration is to develop statistical methods to analyse output from climate and vegetation models. The research is part of the strategic environment ModElling the Regional and Global Earth system (MERGE) which focuses on the terrestrial biosphere (vegetation) to improve local, regional and global climate models. The appointee will also be a part of an already established global network of crop modellers, AgGRID.

Work duties
The aim of this thesis project is to develop statistical emulators for vegetation models (primarily LPJ-GUESS, but also other models from the AgGRID network). The emulators will be used to assess the effect of potential climate change on future crop yields and environmental effects associated to agricultural production and characterise the associated uncertainties. Initial focus will be on combining Gaussian Process regression with standard regression; in a later stage other elements of machine learning might also be considered. Due to the size of the available dataset, computational considerations in designing and running the emulators may become a concern requiring method development.

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%).

Admission requirements

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, or
  • has satisfied the requirements for courses comprising at least 240 credits (4 years) of which at least 60 credits were awarded in the second cycle, or
  • has acquired substantially equivalent knowledge in some other way in Sweden or abroad.

A person meets the specific admission requirements for third cycle studies in Mathematical Statistics if he or she has:

  • at least 90 credits of relevance to the subject, of which at least 60 credits from the second cycle and a specialised project of at least 30 second -cycle credits in subject, or
  • a second-cycle degree in a relevant subject.

Additional requirements:

  • at least one course in Programming.
  • at least one course in Numerical Analysis.
  • at least one course in Stochastic Processes.
  • very good oral and written proficiency in English.

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.

Preference will be given to candidates with:

  • ability (e.g. through a thesis project) to apply relevant statistical models to data and draw appropriate conclusions.
  • experience of interdisciplinary work.
  • experience in spatial statistics and/or machine learning.
  • programming experience with a focus on scientific computing and/or numerical analysis (preferably in Matlab, R, and/or C/C++)

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 §§. First day of employment May 15, 2018 or according to agreement.

Instructions on how to apply
Applications shall be written in English and include a cover letter (not exceeding one page) 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.).

Type of employment Temporary position longer than 6 months
First day of employment May 15, 2018 or according to agreement
Salary Monthly salary
Number of positions 1
Working hours 100 %
City Lund
County Skåne län
Country Sweden
Reference number PA2018/789
  • Johan Lindström, +46462224060
Union representative
  • OFR/ST:Fackförbundet ST:s kansli, 046-222 93 62
  • SACO:Saco-s-rådet vid Lunds universitet, 046-222 93 64
  • SEKO: Seko Civil, 046-222 93 66
Published 16.Mar.2018
Last application date 16.Apr.2018 11:59 PM CET

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