Doctoral student in Software Engineering for AI Applications

The University of Gothenburg tackles society’s challenges with diverse knowledge. 56 000 students and 6 600 employees make the university a large and inspiring place to work and study. Strong research and attractive study programmes attract scientists and students from around the world. With new knowledge and new perspectives, the University contributes to a better future.

The department of Computer Science and Engineering is strongly international, with approximately 300 employees from over 30 countries. The department is a fully integrated department with the University of Gothenburg and Chalmers University of Technology as principals. The position is placed in the Division of Interaction Design and Software Engineering at the department, with the University of Gothenburg as the employer.

Located in Gothenburg – Sweden’s second-largest city – the department is surrounded by a vibrant ecosystem of software-intensive companies. The department is connected to science parks in Gothenburg for industrial collaborations in fields including intelligent vehicles and transport systems, mobile internet, energy, nanotechnology, and life sciences.

The successful candidate will conduct research under the supervision of Dr. Jennifer Horkoff and work in tight collaboration with world-class researchers in the Interaction Design and Software Engineering Division at Chalmers and University of Gothenburg. In particular, the division has a strong Requirements Engineering and AI Engineering focus. The student joins several other PhD students with RE- and ML-related topics.

The Department aims to actively improve our gender balance and we work broadly with equality projects. Equality and diversity are substantial foundations in all activities at the University and Department.

General information about being a doctoral student at the University of Gothenburg can be found on the university's doctoral student pages https://medarbetarportalen.gu.se/doktorand/?languageId=100001&skipSSOCheck=true    

Machine Learning (ML) uses big data to enable software algorithms to “learn” complex patterns in data, solving difficult problems such as recognizing images and diagnosing cancer.  Despite the immense business gains provided by machine learning, there are challenges in its use as part of large, complex software systems: models are opaque and volatile, thus the capabilities of models and training data are difficult to determine upfront, and it is challenging to trace desired behaviours to models and data. Machine learning development must fit into current large-scale agile development practices, including continuous integration and development. These challenges can prevent systems using machine learning from being released or cause critical trust and reliability issues in released systems.

Requirements Engineering (RE) is the sub-field of software engineering that provides concepts, theories, and methods to understand, capture, analyse and manage system needs or requirements through the lifetime of a system. This knowledge guides and coordinates development in large, complex systems. Past project experience supports the hypothesis that new and adapted requirements concepts, theories, and methods can significantly alleviate many of these practical machine learning challenges, allowing for the release of more reliable and trustworthy machine learning systems.

As part of the project, the PhD candidate will tackle a number of potential topics in RE for ML: advance central concepts and theories used in requirements, create new development methods considering agility and machine learning, enable requirements-driven continuous deployment and integration of machine learning models, produce development methods to handle requirements-level machine learning uncertainty, expand software traceability to include new concepts, and develop requirements methods over the data needed for machine learning. These achievements will facilitate further advances in requirements for ML, allowing for effective development of complex software systems with ML.  The PhD will focus on a sub-set of these topics within RE for ML, depending in part on the interest and expertise of the candidate.

Third-cycle studies comprises four years of full-time studies and leads after a successful completion to a Degree of Doctor of Philosophy in Computer Science and Engineering. Those who are employed as doctoral students must primarily devote themselves to their doctoral education. However, a doctoral student may to a limited extent work with education, research and administration, so-called departmental service in a teaching or supporting role, which can be concentrated on certain parts of the year depending on the needs of the business in consultation with the student. Such work may, before the doctoral degree is completed, not cover more than 20 percent of full-time work over the study period. If departmental service is performed corresponding to 20 percent of full-time study time, the employment contract is extended by the corresponding period, which gives a total employment of five years.

The purpose of the education is for the doctoral student to acquire the knowledge and skills required to be able to conduct independent research in the field of service, and to contribute to the development of knowledge in the subject by writing a scientific dissertation. The doctoral education is in total 240 higher education credits and includes thesis work corresponding to 180 higher education credits and courses corresponding to 60 higher education credits.

More specifically, successful candidates will read, review, and write research papers; give presentations; take courses; conduct systematic literature reviews; design and conduct empirical studies; interact with industrial companies; and perform quantitative and qualitative data analysis.  The student will become familiar with, evaluate and apply techniques related to requirements engineering (RE); and will become familiar with the space of machine learning (ML), including different algorithms, contexts, data preparation strategies, and challenges.  Although the focus is primarily on research, the candidate will also be involved in teaching and administration, including course assistance, membership on committees, and supervision of bachelor and master’s theses.   The aim is to prepare the candidate to be a successful, independent researcher. 

Education at third-cycle level requires general eligibility and, where appropriate, specific eligibility as set out in the general syllabus for the subject.  

The general eligibility requirements for education at third-cycle level are:

Specific entry requirements for this subject, according to the general syllabus, are:
To be qualified for admission to third-cycle program in Computer Science and Engineering the applicant is required to have obtained a second-cycle qualification. The orientation of the student’s degree shall have a sufficiently close connection to the subject of computer science and engineering. Equivalent requirements apply to individuals who have been awarded their degree in a country other than Sweden.

Further desirable but not mandatory criteria include previous research experience including publications in international, peer-reviewed venues; a Master’s degree in a related subject; expertise in software engineering, knowledge of artificial intelligence and machine learning; and knowledge of requirements engineering, including concepts and techniques.

The candidate is expected to have advanced English skills in reading and writing, equivalent to at least the C1 Level in English of the Common European Framework of Reference for Languages.

The selection of applicants who meet the basic and specific eligibility requirements will be based on the ability to assimilate the education at third-cycle level.   

Once you have been admitted for education at third-cycle level, you will be employed as a doctoral student at the University of Gothenburg. The provisions for employment as a doctoral student can be found in ordinance SFS 1993:100. Initial employment as a doctoral student may apply for a maximum of one year and may be renewed by a maximum of two years at a time. A doctoral student may be employed as a doctoral student for a maximum of eight years, but the total period of employment may not be longer than the equivalent of full-time education at third-cycle level for four years.   

The University applies a local agreement on salaries for doctoral students. 

Type of employment: Fixed-term employment, HF 5 kap 7 §
Extent: 100 % of full time
Location: Department of Computer Science and Engineering /Division of Interaction Design and Software Engineering
First day of employment: 2023-09-01 or as soon as possible 

Regarding the project, please contact Jennifer Horkoff (e-mail: [email protected] ).
Regarding the position, please contact Palle Dahlstedt (e-mail: [email protected] ).
Regarding the appointment procedure, please contact HR-partner Robin Garnham (e-mail: [email protected] ).

Union representatives at the University of Gothenburg can be found here:
https://www.gu.se/om-universitetet/jobba-hos-oss/hjalp-for-sokande    

You can apply to be admitted for education at third-cycle level via the University of Gothenburg’s recruitment portal. It is your responsibility to ensure that the application is complete as per the vacancy notice, and that the University receives it by the final application deadline. 

The application is to be written in English.

Applications must be received by: 2023-04-24 

Choosing a career in a foreign country is a big step. Thus, to give you a general idea of what we and Gothenburg have to offer in terms of benefits and life in general for you and your family/spouse/partner please visit: 

https://www.gu.se/en/about-the-university/welcome-services
https://www.movetogothenburg.com/  

The University works actively to achieve a working environment with equal conditions, and values the qualities that diversity brings to its operations.

Salaries are set individually at the University.

In accordance with the National Archives of Sweden’s regulations, the University must archive application documents for two years after the appointment is filled. If you request that your documents are returned, they will be returned to you once the two years have passed. Otherwise, they will be destroyed.

In connection to this recruitment, we have already decided which recruitment channels we should use. We therefore decline further contact with vendors, recruitment and staffing companies.

Read more and apply here; https://web103.reachmee.com/ext/I005/1035/job?site=7&lang=UK&validator=9b89bead79bb7258ad55c8d75228e5b7&job_id=29561