Lund University, Faculty of Engineering, LTH, Centre for Mathematical Science

Lund University was founded in 1666 and is repeatedly ranked among the world’s top 100 universities. The University has 40 000 students and more than 8 000 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
The aim of this project is to develop techniques monitoring and diagnosing various health problems using vocal changes. The work will focus on statistical and audio signal processing as well as machine learning, areas where a successful candidate is expected to have strong prior experience. The project is an ELLIIT-funded collaboration between researchers at Lund University and Blekinge Institute of Technology, with one Ph.D. student recruited at each site, and will involve both inter- and cross-disciplinary research related to signal processing, medicine, and speech therapy.

The aim of this project is to develop signal processing and machine learning techniques that allow for a combination of measured longitudinal audio signals and patient information to monitor disease progression and diagnose several forms of diseases that affects a persons voice, such as, for instance, Neurocognitive disorders ((cognitive decline), pulmonary disorder (COPD), and heart failure conditions.

To accomplish this, the student will develop and use modern statistical signal processing and machine learning techniques. Computational 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 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 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, Optimization, Stochastic Processes, 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 of interdisciplinary work.
  • experience in statistical and/or audio signal processing, optimization and machine learning.
  • programming experience with a focus on machine learning (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.).

Type of employment Temporary position longer than 6 months
First day of employment According to agreement
Salary Monthly salary
Number of positions 1
Working hours 100
City Lund
County Skåne län
Country Sweden
Reference number PA2021/445
Contact
  • Andreas Jakobsson, professor, andreas.jakobsson@matstat.lu.se,
Published 15.Mar.2021
Last application date 12.Apr.2021 11:59 PM CET

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