Doctoral students in Mathematics with a focus on Computer Vision - Hiring in process/Finished, not possible to apply

Description of the workplace

The positions will be placed at the Division of Computer Vision and Machine Learning (CVML) at the Centre for Mathematical Sciences. The Centre for Mathematical Sciences is a department affiliated with both the Faculty of Engineering (LTH) and the Faculty of Science at Lund University. Within CVML there are several senior researchers and approximately 20 PhD students. Research in the field 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 PhD student will be employed at CVML but will also be a part of the WASP graduate school.

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.

Read more: Wallenberg AI, Autonomous Systems and Software Program

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.

Read more: Graduate School

Research subject

The research subject for the current call is mathematics with a focus on computer vision and machine learning. The anouncement consists of two projects listed below. State in your application which of the two projects you are interested in. You may apply for both.

1. Matrix factorization and optimization. Factorization methods are important building-blocks in many engineering applications. Their ability to extract compact low dimensional models from matrix/tensor-organized data is of key importance in areas such as computer vision and machine learning. Our overall goal is to understand when this possible, through theoretical studies of optimization formulations, and to design reliable and efficient algorithms that converge to the right solution independently of initialization. An application of interest is the so-called Structure from Motion problem. Here a set of points tracked through a collection of images are used to compute the camera motion as well as a model of the potentially dynamic scene.
   Contact: Carl Olsson, carl.olsson@math.lth.se
2. Differentiable neural acoustics. This project involves 3D mapping methods used to enable localization and navigation primarily using sound, but possibly also using radio. The input data consists, for example, of a number of sound signals from which the 3D geometry of transmitters, receivers, and acoustic properties in the environment are calculated. In the research, we develop and use a large number of techniques for example for parameter estimation, optimization, machine learning, drawing inspiration from the latest results in computer vision and machine learning.
   Contact: Kalle Åström, karl.astrom@math.lth.se

The thesis work in both projects 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.

The work duties include:

• Participation in doctoral courses.
• Work within one of the research projects, with an increasing degree of independent research.
• 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 specialized 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 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:

Knowledge and skills relevant to the thesis project and the subject of study. An assessment of ability to work independently and to formulate and tackle research problems. Written and oral communication skills. Other experience relevant to the third-cycle studies, e.g. professional experience.

Other assessment criteria:

• Experience in Mathematical Optimization and Matrix Theory.
• A project-relevant master's thesis.
• Good programming skills in Matlab, Python or C++.
• Skills in Computer Vision or Machine Learning relevant for the project.
• Experience in machine learning frameworks (PyTorch, TensorFlow or equivalent).

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

Welcome to apply!