Vacant job

Lund University was founded in 1666 and is consistently ranked among the world's leading universities. There are approximately 46,000 students and 8,500 staff members in Lund, Helsingborg, and Malmö. We are united in our strive to understand, explain, and improve our world and the conditions of people.

Description of the activity

The Department of Electrical and Information Technology conducts internationally outstanding research in a wide range of areas, spanning from purely theoretical research to applied projects in close collaboration with industry. It is at the forefront of international research in most of its fields. The department consists of approximately 100 active researchers focusing on several research domains, including security and network systems, communication technology, integrated electronic systems, electromagnetics and nanoelectronics, as well as intelligent systems and machine learning.

We are now looking for a new doctoral student for work in a WASP-funded project.

Being a doctoral student

As a doctoral student, you are both admitted as a student and employed at Lund University.

As a research student, you are trained in a scientific approach. This can be briefly described as gaining practice in thinking critically and analytically, solving problems independently using the right methodological choices, and developing research ethical awareness. Additionally, as a doctoral student, you are given the opportunity to work on projects, develop your leadership skills, and enhance your pedagogical abilities. Throughout your studies, you are guided by supervisors. The doctoral studies conclude with a thesis and a doctoral degree.

More about being a doctoral student at LTH on lth.se.

Subject and project description

Machine learning and artificial intelligence have attracted significant attention over the past few decades. Machine learning algorithms have been used in many application domains, including the Internet of Things (IoT), autonomous systems, medical applications, and healthcare applications. The use of machine learning in these domains creates many new opportunities but also entails several major challenges, such as the complexity of machine learning algorithms and the reliability and trust in decisions made by machine learning algorithms.

The Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden's largest single research program in modern times. The program creates a platform for academic research and education in close collaboration with leading Swedish technology-intensive industry. The research includes artificial intelligence and autonomous systems that operate in collaboration with humans and adapt to their surroundings using sensors, information, and knowledge, creating intelligent systems of systems. WASP's vision is excellent research and competence in artificial intelligence, autonomous systems, and software for the benefit of Swedish industry.

More about WASP (wasp-sweden.org).

The doctoral school within WASP aims to equip future researchers with the necessary knowledge to analyze, develop, and actively contribute to the interdisciplinary development of artificial intelligence, autonomous systems, and software. Through an ambitious program featuring research visits, partner universities, and guest lecturers, the doctoral school actively supports the formation of a strong multidisciplinary and international professional network between doctoral students, researchers, and industry. The doctoral school thus offers a unique opportunity for students attracted by world-class international research with industrial relevance.

More about WASP's doctoral school (wasp-sweden.org/graduate-school).

Tasks

You will primarily focus on your doctoral education, which includes participating in research projects as well as doctoral education courses, seminars, and conferences.

You will work in the field of machine learning for IoT systems to address the biggest challenges in the machine learning field, such as the complexity of machine learning algorithms, reliability, and trust. A key part of the work is to develop the theoretical foundation for reliable machine learning and new algorithms to handle challenges within this environment. You will validate these theoretical methods and algorithms through experiments and simulations.

The tasks also include participation in teaching and other departmental work (however, max 20% of working time).

Qualifications

To be admitted and employed as a doctoral student, you must meet the requirements below.

For the full advertisement, please see https://lu.varbi.com/what:job/jobID:937569/ (https://lu.varbi.com/what:job/jobID:937569/).