Doctoral student in Mathematical Statistics with a focus on Sonar Signal Processing - Hiring in process/Finished, not possible to apply

Description of the workplace

The workplace is the division of Mathematical Statistics with approximately 25 teachers, researchers and doctoral students. Research areas within mathematical statistics are probability theory and statistical theory. The main task of probability theory is to develop mathematical models for the description and analysis of random processes, and to study the mathematical properties of such models. Within the statistical theory, principles and methods are studied to build and test the models with the help of empirical facts and data. Applications are found in all areas of society with an emphasis on science, technology, medicine and economics.

Project description

Recent events have highlighted the vulnerability of critical underwater infrastructure, such as gas pipelines and submarine cables. To increase the protection of our society and our marine environment, it is therefore of great importance that new scalable technologies are developed for reconnaissance and communication in underwater environments.
 
This research project is carried out in close collaboration with researchers at KTH and FOI and aims to develop improved sonar signal processing with a focus on both theory and method development for reconnaissance in underwater environments. 

The project is implemented within Wallenberg AI, Autonomous Systems and Software Program (WASP). Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry.

More information about WASP (wasp-sweden.org)

The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry.

More information about WASP graduate school (wasp-sweden.org/graduate-school)

Work duties

The main task of a doctoral student is to devote himself or herself to his or her doctoral education, which includes participation in research projects as well as doctoral courses. The research concerns both theoretical and methodological development in sonar signal processing, with a focus on optimal mass transport, sparse structures, multi-dimensional signal processing and convex optimization.

The duties also include participation in teaching and other institutional work at Mathematical Statistics, but a maximum of 20% of the working hours.

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 specialized 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 and one course in Optimization,
• at least one 2nd cycle course in Stochastic processes, Machine learning, or related subjects such as: Time-series analysis, Spatial statistics, Spectral analysis, Statistical 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.

Other assessment criteria:

• ability (shown via, e.g., a thesis project) to develop, implement, and apply relevant scientific statistical models to data and critically assessing the results
• experience in signal processing and time series analysis
• programming experience (preferably in Python or Matlab).

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant, through experience and skills, is deemed to have the abilities necessary for successfully completing the third cycle programme. 

We offer

Lund University is a public authority which means that employees get particular benefits, generous annual leave and an advantageous occupational pension scheme. Read more on the University website about being a Lund University employee Work at Lund University. 

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 §§.

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.).

Welcome to apply!