Skilled and committed employees are a crucial factor in the success of Linköping University. And we need more of them. Our core expertise comes from teachers and researchers, but a successful university requires experienced and motivated employees in many fields. Everyone is important. We need to recruit many new employees thanks to, among all, an expansion in our research activity. We need you here. We look forward to receiving your application!
The department of Electrical Engineering (ISY) is central to the engineering education at the Institute of Technology, one of four faculties at Linköping University, and this regards both basic and applied knowledge. The research is based on industrial needs, and ranges from basic research to direct application in collaboration projects.
Read more at https://liu.se/en/organisation/liu/isy
We are looking for a PhD student in Joint Sensor Fusion and Machine Learning for Autonomous Systems.
Your work assignments
The control-oriented research at Linköping University concerns different topics such as sensor fusion, learning methods for control, and optimization. We are currently looking for PhD students to work within the Wallenberg AI, Autonomous Systems and Software Program (WASP), where they will conduct research on how to combine machine learning methodology with classic statistic signal processing.
Project description: Methods for distributed learning of augmented state-space models will be researched. This class of models enables domain knowledge to be incorporated in the learning process to guarantee a minimum of performance and enable an efficient learning process; still, they are flexible enough to permit learning of partially unknown model dynamics and inputs. Thus, the targeted methods are foreseen to play an important role in realizing large-scale sensing systems. Focus of the research will be on learning of state-space models augmented with sparse Gaussian process models. To enable distributed and efficient learning of the models, techniques for distributed Gaussian process regression, such as Bayesian commit machines and inner product quantization, will be integrated with distributed filter algorithms, such as covariance intersection, consensus, and diffusion Kalman filters. The use of information-gain based active learning strategies to streamline the learning process, both on local and global scale, will be investigated.
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 industry. Read more: wasp-sweden.org
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: wasp-sweden.org/graduate-school
As a doctoral student, you devote most of your time to doctoral studies and the research projects of which you are part. Your work may also include teaching or other departmental duties, up to a maximum of 20% of full-time.
The Division of Automatic Control at Linköping University carries out research, undergraduate and postgraduate education within control, sensor fusion, system identification, autonomous systems, robotics, complex networks, optimization, and learning control. Read more: control.isy.liu.se/en
You have graduated at Master’s level electrical engineering, engineering physics, or applied mathematics or similar or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced courses within the same topics. Alternatively, you have gained essentially corresponding knowledge in another way.
Furthermore, you are eager to learn new things and explore the unknown and like to pay attention to details. You can comfortably express yourself in English and know how to convey a message in written text.
Terms of employment
When taking up the post, you will be admitted to the program for doctoral studies. More information about the doctoral studies at each faculty is available at Doctoral studies at Linköping University
The employment has a duration of four years full-time equivalent. You will initially be employed for a period of one year. The employment will subsequently be renewed for periods of maximum duration two years, depending on your progress through the study plan. The employment may be extended up to a maximum of five years, based on the amount of teaching and departmental duties you have carried out. Further extensions can be granted in special circumstances.
Salary and employment benefits
The salary of doctoral students is determined according to a locally negotiated salary progression.
More information about employment benefits at Linköping University is available here.
Information about union representatives, see Help for applicants.
Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than July 7, 2022.
Applications and documents received after the date above will not be considered.
We welcome applicants with different backgrounds, experiences and perspectives – diversity enriches our work and helps us grow. Preserving everybody’s equal value, rights and opportunities is a natural part of who we are. Read more about our work with: Equal opportunities.
We look forward to receiving your application!
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Post expires on Sunday July 10th, 2022