Doctoral student in mathematical statistics focused on statistical signal processing - Hiring in process/Finished, not possible to apply

Project description

The aim of this project is to develop techniques for estimating, interpolating, and extrapolating sound fields as well as methods for active noise cancellation techniques able to create quiet sound zones, for instance in an office environment. The work will integrate topics such as statistical, sparse, and acoustic signal processing as well as machine learning-omputational and memory considerations may become a concern, requiring method 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 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 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.

Finally, the student must be judged to have the potential to complete the programme.

Additional requirements:

• at least one course in Programming, Time Series Analysis, and Machine Learning.
• 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: 

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. 

Preference will be given to candidates with:

• ability (shown via, e.g., a thesis project) to apply relevant statistical models to data and draw appropriate conclusions.
• experience in statistical, sparse, and acoustic signal processing, optimization and machine learning. 
• programming experience (preferably in Matlab and/or Python)

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.). 

You are also asked to answer the selection questions.