Doctoral student in Mathematics with focus in Machine Learning Methods - Hiring in process/Finished, not possible to apply

Description of the workplace

The Centre for Mathematical Sciences consists of about 150 teachers, researchers and doctoral students. Staff at the department provides graduate training and research activities within many different areas of mathematics. You will belong to the Division of Computer Vision and Machine Learning.

Subject description: Description and spatio-temporal analysis of remote sensing signals

The research work will focus on the development of machine learning methods for anomaly detection and spatio-temporal analysis of mixed data including geospatial visible and multi-spectral signals. The research group will work with:

• ways to describe correlations and noise in the data; 
• design of improved loss functions which enhance spatial-temporal analysis of information from remote sensing (GIS/satellites/drones);
• design of improved autoencoders (VAEs, GANs), diffusion models and other such machine learning methods towards analysis and detection of anomalies as well as identifying important features of a learned probability distribution in latent space. 

Analysis through information theory tools such as the relative entropy rate and the Fisher information matrix can be useful metrics in some of the above tasks. This work has diverse applications in image processing and analysis ranging from predicting yield to uncovering detailed carbon sequestration profiles over larger geographical regions.

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 mathematics if the applicant has:

• at least 90 credits of relevance to the subject area, of which at least 60 credits from the second cycle and a specialised project of at least 30 second-cycle credits in the field, or a second second-cycle degree in a relevant subject.

In practice, this means that the student should have achieved a level of knowledge in mathematics that corresponds to that of a Master of Science programs in Engineering Mathematics or Engineering Physics, alternatively a Master’s degree in mathematics or applied mathematics.

Additional requirements:

• 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 assessed 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:

• Programming skills and experience with machine learning/deep learning.
• Experience with data analysis and spatial statistics.
• Familiarity with GIS- and remote sensing methods.

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!