Doctoral student in Applied Mathematics with a focus on Computer Vision

Description of the workplace

The position will be placed at the division of Computer Vision and Machine Learning at the Centre for Mathematical Sciences. The Centre for Mathematical Sciences is an institution affiliated with both the Faculty of Engineering (LTH) and the Faculty of Science at Lund University. Within the division of Computer Vision and Machine Learning, there are several senior researchers and approximately 20 doctoral candidates. Research in computer vision began in the mid-1980s and currently encompasses (i) Geometry and computer vision (including analysis of video, audio, radio, and radar signals), (ii) Medical image analysis, and (iii) Machine learning/artificial intelligence. The group boasts extensive experience in fundamental research within computer vision, machine learning and artificial intelligence, as well as a track record of translating such findings into practical applications for end-users. The position is funded by WASP (https://wasp-sweden.org), which means that the PhD student will benefit from being part of the WASP-network.

Subject description

The research subject for the current call is mathematics with a focus on computer vision and machine learning. The announced position is within the WASP-funded project ”Differentiable Neural Acoustics”.

Within our division, we have extensive experience in developing new methods for creating 3D models from sensor data, which are used in many applications, 3D maps for human navigation, mapping and localization for autonomous cars and other vehicles. We develop new methods, for example, feature extraction from sensor data, solving polynomial equations, and optimization. In this project, we will also explore new methods for 3D modeling and sensor position estimation that operate directly on sensor data. Here, we will also use new so-called feature-metric approaches. These new modern deep-learning based approaches have the potential of revolutionizing the geometric understanding. We will in the project primarily study acoustic data and sensors, but the methods could also be applied to other sensor types. 

The thesis work in the project will include the development of new methods, theoretical analysis, algorithm design, planning and execution of experiments, data collection, writing scientific articles, and presenting the results at international conferences.

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%). 

This project concerns 3D mapping methods used to enable localization and navigation primarily by means of sound, but possibly also by radio. The input data is typically a number of sound signals from which the 3D geometry of transmitters, receivers and acoustic properties in the environment are calculated. The thesis work will include the development of new methods, planning and execution of experiments, data collection, programming and implementation, writing scientific articles, and presenting the results at international conferences.

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 Applied mathematics if the applicant has: 

• at least 90 credits of relevance to the subject area, of which at least 60 credits are from the second cycle and include a specialised project of at least 15 credits in the field, or
• a second-cycle degree in a relevant field

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 or 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 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:

• Good programming skills in Python or C++
• Experience in machine learning frameworks (for example PyTorch)
• Skills in computer vision or machine learning relevant for the project 

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, grade transcript and other documents you wish to be considered (contact information for your references, letters of recommendation, etc.).

Welcome to apply!