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We are looking for a PhD student in Critical Software-Intensive Systems within 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 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.
Your work assignments
Due to the heterogeneous nature of data science teams, machine learning (ML) researchers and practitioners often come from various disciplines with limited expertise in writing high quality ML software. However, neglecting best practices for software quality assurance results in unmaintainable, inefficient and non-modular ML programs. Compared to traditional software, ML code quality is more challenging to manage as deficiencies may lead to silent pitfalls that perdure for long time and require significant time and effort to discover. As a specific quality concern, code smells are commonly appearing poor code design choices that violate best software engineering practice and have negative effects on various quality attributes (such as maintainability, scalability).
This PhD project aims to develop efficient novel techniques and scalable software tools for automatically detecting and removing various classes of anti-patterns in complex ML programs. The project plans to combine traditional graph-based detection techniques with machine learning solutions to ensure that the most critical anti-patterns are always detected while false alarms are rare.
Your involvement in the development and maintenance of a related open-source software project is foreseen in close collaboration with other researchers and graduate students in Sweden, Canada and Hungary.
As a PhD 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.
You have graduated at Master’s level in Computer Science, Software Engineering, Computer Engineering, Artificial Intelligence or Applied Mathematics with a minimum of 240 credits, at least 60 of which must be in advanced courses in Software Engineering or Computer Science. Alternatively, you have gained essentially corresponding knowledge in another way.
As an applicant, you must have very good software engineering and/or machine learning skills and mathematical maturity. You shall also have very good English skills, both orally and in writing to facilitate publication at leading scientific venues of software engineering and/or machine learning. Early research experience during master’s or undergraduate studies is further advantageous.
The Department of Computer and Information Science was founded in 1983 but its roots go back to the early 1970s. It is one of the largest computer science departments in northern Europe.
Our research covers a broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in several engineering programmes at bachelor’s and master’s levels, as well as the programmes in statistics, cognitive science and innovative programming.
Read more at https://liu.se/en/organisation/liu/ida
The position in placed in the Division for Software and Systems (SaS), welcome to read more about us at https://liu.se/en/organisation/liu/ida/sas. Core research areas in SaS include software engineering, programming environments, systems software, embedded SW/HW systems, computer systems engineering, real-time systems and theoretical computer science.
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.
Starting date by agreement (potentially starting from August 21, 2023, or later).
Salary and employment benefits
The salary of PhD 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 June 12, 2023.
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! Linköping university has framework agreements and wishes to decline direct contacts from staffing- and recruitment companies as well as vendors of job advertisements.
Dániel Varró, WASP Professor, firstname.lastname@example.org
Sofie Bondesson, HR-administrator email@example.com