Doctoral student in Computer Science with specialisation in Software Engineering - Hiring in process/Finished, not possible to apply

Project description
This project aims to design software engineering methods and tools to govern business-to-business (B2B) data ecosystems.  With the emergence of machine learning (ML) techniques into Industry 4.0 applications, the volumes of data required to train ML applications grow. Sharing data between multiple organisations in their engineering of software and systems may be of mutual benefit but has to be balanced with the business values, be supported by tools for data access and maintenance, and preserve integrity/security of the data sources.

For open source software (OSS), tools like Git, Jenkins and Gerrit, provide a low-threshold entry to support distributed versioning, reviews and testing. This project aims to understand the needs for corresponding methods and tools in B2B data sharing and design solutions accordingly. This includes support for versioning, encryption, differential privacy, licensing, maintaining and collaborating around shared data sets, aligning to the business models for such data sharing in Industry 4.0.

The doctoral student position is part of the research project “B2B Data Sharing for Industry 4.0 Machine Learning”, which also includes a parallel PhD project on business model innovation at Linköping University. It is funded by ELLIIT, a strategic research environment funded by the Swedish government. ELLIIT constitutes a platform for research and for cross-fertilization between disciplines and between academic researchers and industry experts. ELLIIT stands out by the quality and visibility of its publications, and its ability to attract and retain top talented researchers, and aims at being recognized as a top international research organization.

Work duties
The PhD position lasts consists of three main aspects:

• research project, including trips to conferences, seminars etc.,
• postgraduate courses, locally and internationally given (90 credits), and
• teaching (at most 20%), including lab supervision and exam responsibilities. This part also involves professional development working with equality and diversity, arranging events etc.

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 he or she 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:

• Very good knowledge about software engineering theory and practice
• Very good oral and written proficiency in English.
• The ability to work both independently and in small teams

Assessment criteria
Selection for third-cycle studies is based on the student’s potential to profit from such studies. The assessment of potential is made primarily on the basis of academic results from the first and second cycle. Special attention is paid to the following:

1. Knowledge and skills relevant to the thesis project and the subject of study.
2. An assessment of ability to work independently and to formulate and tackle research problems.
3. Written and oral communication skills
4. Other experience relevant to the third-cycle studies, e.g. professional experience.

Other assessment criteria:

• Industrial experience, particular in Industry 4.0 context
• Open source software contributions
• Knowledge and skills in configuration management of software
• Good programming skills
• Understanding of machine learning and artificial intelligence

Consideration will also be given to good collaborative skills, drive and independence, and how the applicant, through his or her experience and skills, is deemed to have the abilities necessary for successfully completing the third cycle programme.

Terms of employment
Only those admitted to third cycle studies may be appointed to a doctoral studentship. Third cycle studies at LTH consist of full-time studies for 4 years. A doctoral studentship is a fixed-term employment of a maximum of 5 years (including 20% departmental duties). Doctoral studentships are regulated in the Higher Education Ordinance (1993:100), chapter 5, 1-7 §§.

Instructions on how to apply
Applications shall be written in English and include a cover letter stating the reasons why you are interested in the position and in what way the research project corresponds to your interests and educational background. The application must also contain a CV, degree certificate or equivalent, and other documents you wish to be considered (grade transcripts, contact information for your references, letters of recommendation, etc.).