Doctoral student in Computer Science with a focus on Sensor Fusion for Multi-task Learning Full-time

Doctoral Student In Computer Science With A Focus On Sensor Fusion For Multi-Task Learning

Lund University was founded in 1666 and is repeatedly ranked among the world's top universities. The University has around 47,000 students and more than 8,800 staff based in Lund, Helsingborg, and Malmö. We are united in our efforts to understand, explain, and improve our world and the human condition.

Lund University welcomes applicants with diverse backgrounds and experiences. We regard gender equality and diversity as a strength and an asset.

Description Of The Workplace

The division for Robotics and Semantic Systems (RSS) consists of several, tightly collaborating research groups conducting research and education in Robotics and AI, Intelligent Autonomous Systems, Robot Learning, Machine Learning, Human-Robot Interaction, and Natural Language Processing. The division runs, together with the Department for Automatic Control, the RobotLab LTH, a research and education facility equipped with a multitude of robotic and related systems, ranging from small drones and UAVs to classic industrial manipulators. The research topics also include, and this within national and international cooperations with academic and industrial partners, areas like autonomous cars or ships.

The overall goal for the researchers in RSS is to build intelligent autonomous (robotic) systems, i.e. equip the different types of systems with skills and knowledge that enable a smoother collaboration and interaction with humans in various contexts. The division consists currently of approximately 20 employees, of which about 10 are PhD students. This makes RSS one of the larger divisions within the department.

Being A Doctoral Student

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

As a doctoral student, you will be trained in a scientific approach. In short, you will be trained to think critically and analytically, to solve problems independently using the right methods, and to develop an awareness of research ethics. In addition, you will have the opportunity to work on projects, to develop your leadership and pedagogical skills. Throughout your studies, you will be guided by supervisors. Doctoral studies end with a thesis and a doctoral degree.

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

Subject And Project Description

The PhD project lies in the area of sensor fusion for multi-task learning and will be supervised by Assoc. Prof. Eren E. Aksoy. The project will be part of a collaborative project with a research group at Linköping University (headed by Assoc. Prof. Gustaf Hendeby). This project targets developing a multimodal multitask learning framework for reliable robot situational awareness in adverse environmental conditions. The PhD program for the project part at Lund University is Computer Science. The research focuses on developing advanced AI methods for multi-modal sensor fusion (e.g., 2D RGB images and 3D point clouds) to jointly optimize complementary downstream perception tasks, such as object detection and semantic segmentation.

We are looking for a person with enthusiasm for the practical work within Robotics, still having a solid educational background within AI and Machine Learning, who has good theoretical and mathematical skills and knowledge, and who is keen on driving further the work with the next generation's robotic systems, that can learn multiple perception tasks using various sensor modalities.

More about ELLIIT at elliit.se.

Work Duties

You will primarily devote yourself to your doctoral programme, which includes participation in research projects as well as third cycle courses, seminars, and conferences. The duties also include participation in teaching and other departmental work (however, a maximum of 20% of working hours). The employment period is then extended accordingly. The employment as PhD student includes also travel, for example to conferences or project meetings with the project partners in Linköping. It is further assumed that you participate actively in the annual ELLIIT Workshop.

More about the annual ELLIIT Workshop at elliit.se.

Qualifications

To be eligible for admission and employment as a doctoral student, you must fulfil the requirements below.

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 Computer Science if the applicant has:

• at least 60 second-cycle credits at an advanced level with relevance for the research topic, or
• an MSc in Engineering in Computer Science and Engineering, Electrical Engineering, Information and Communication Technology, Engineering Physics, or Engineering Mathematics.

Additional Requirements

In order to complete the doctoral programme in question, also the following requirements must be met:

• good mathematical skills
• good programming knowledge
• good ability to work independently and to formulate and tackle research problems.
• good written and oral communication skills
• good ability to cooperate
• capability to take initiative
• very good knowledge of English, spoken and written
• documented knowledge in Artificial Intelligence beyond Machine Learning (including Cognitive Science)
• documented knowledge in Machine Learning / Deep Learning

Other Qualifications

For the doctoral programme in question, the following are considered as other qualifications:

• documented knowledge within robot perception or related fields (e.g. sensor fusion and semantic scene understanding)
• experience with system and tools like ROS / ROS2 and PyTorch

We Offer

Lund University is a public authority which means that employees get particular benefits, generous annual leave, and an advantageous occupational pension scheme. The Department of Computer Science and RSS is part of several local and national networks to which you will get access and within which you will have the opportunity to collaborate with fellow PhD students and other researchers from various research fields, academic sites, and industry.

More about working at Lund University on lu.se.

About The Employment

The employment is a fixed-term employment at full time, starting as soon as possible by agreement, however no later than December 15, 2026.

Third cycle studies at LTH consist of full-time studies for 4 years. In the case of teaching and other departmental duties, the employment is extended accordingly. Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

More about terms of employment for doctoral students on Lund University's Staffpages.

Other

When the call is closed and the submitted applications have been assessed, a small group of selected candidates will be called into a first interview, most often conducted online. Depending on the number of submissions, this can take several weeks. Based on the first interview an even smaller group of applicants will be invited to participate in a personality test and work with a task related to the position to prepare for a second follow-up interview. With a high probability, also this will be conducted online. All application material including updates submitted by the deadline will be considered.

How To Apply

Applications shall be written in English and include:

• CV and a cover letter stating the reasons why you are interested in the doctoral programme/employment and in what way the research project corresponds to your interests and educational background.
• Copies of issued study certificates and/or awarded degree certificates. These must confirm that you meet the general and specific admission requirements for the doctoral programme and show that you have the subject knowledge required for the doctoral programme project.
• Other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.)

We welcome your application.