Doctoral student in mathematical statistics - Hiring in process/Finished, not possible to apply

Project description
The PhD project is in the area of theoretical inference. The project consists of method development in nonparametric statistical  inference, and in particular in order restricted statistical inference in several dimensions. The projects goal is to derive new algorithms for the inference problem and to derive theoretical properties for said algorithms, such as e.g. limit distributions, consistency, rates of convergence. The theoretical mathematical problems have important applications to problems in medicine, biology, law and physics, and a part of the project may consist of a study of consequences of the derived theoretical results to these areas. The emphasis of the project is on theory development.

Work duties
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 can 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 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 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:

• Very good oral and written proficiency in English.
• Passed courses on topology and measure theory/integration theory.

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:

1. Knowledge and skills relevant to the thesis project and the subject of study.
2. An assessment of ability to work independently and to formulate and tackle research problems.
3. Written and oral communication skills
4. Other experience relevant to the third-cycle studies, e.g. professional experience.

Other assessment criteria:

• Demonstrated will and ability to do research in mathematics and mathematical statistics gives preference.
• Passed PhD level courses in nonparametric inference and weak convergence give preference.
• Passed PhD level courses on probability theory, inference theory, nonparametric inference and weak convergence are desirable.
• Proficiency in C++ and R is desirable.

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.).