Doctoral student in Mathematical Statistics - Hiring in process/Finished, not possible to apply

Work duties
The aim of this thesis project is to develop spatial statistical models and inference methods that can be applied to a wide array of environmental data and improve the performance of a wave power plant; possible applications include prediction of waves, reconstruction of past vegetation, estimates of CO2 emissions and analysis of climate model output. Additionally wave predictions will be used in conjunction with stochastic control algorithms to improve the control, and thus performance, of a wave power plant.

This position is part of a collaboration between Mathematical Statistics, the company Waves4Power, and the strategic research area ModElling the Regional and Global Earth system (MERGE) at Lund University.

To accomplish this the student will develop and use modern statistical methods in spatial statistics, simulation based inference and stochastic optimization. Due to the size of the available datasets and speed requirements of the control algorithms, computational considerations in designing and running the algorithms 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 the applicant:

• 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 the applicant has:

• at least 90 credits of relevance to the subject, of which at least 60 credits (1 year) from the second cycle and a specialised project of at least 30 second-cycle credits in the 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 stochastic process, stochastic optimization and/or spatial statistics.
• programming experience with a focus on scientific computing and/or numerical analysis (preferably in Matlab, R, Python, 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 §§.

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.).