PhDInformatics Engineering
| Study location | Lithuania, Vilnius, On Campus |
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| Academic field | Computer science (ISCED 481) |
| Type | Doctoral, full-time |
| Nominal duration | 4 years (30 ECTS) |
| Study language | English |
| Awards | PhD (PhD candidate position in “Research on a fuzzy reasoning and machine learning-based automation of a complex and dynamic systematic literature review process”) |
| Course code | Informatics Engineering T007 |
| Application fee | €100 one-time |
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| Entry qualification | Postgraduate diploma (or higher) The entry qualification documents are accepted in the following languages: English. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. You must take verified copies of the entry qualification documents along with you when you finally go to the university. |
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| Language requirements | English International applicants to whom English is not a native language need to provide a proof of their English language proficiency. Exceptions are made only for applicants who have completed their previous studies fully in English. One of the following is accepted: |
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| Other requirements | At least 2 reference(s) must be provided. - Certified copies of the Master’s degree diploma and its supplement with grades or higher education equivalent to it; |
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| More information |
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Overview
PhD candidate position in “Research on a fuzzy reasoning and machine learning-based automation of a complex and dynamic systematic literature review process”
Open application for a doctoral candidate in Informatics Engineering
The doctoral candidate position is available in the Faculty of Fundamental Sciences, Department of Information Systems. Applicants interested in other research topics related to “Research on a fuzzy reasoning and machine learning-based automation of a complex and dynamic systematic literature review process” are also welcome to apply.
Research topic description
Systematic literature reviews (SLRs), which are conducted to gather and summarize knowledge from existing scientific publications and identify gaps for new research opportunities, are popular and needed in the research field. However, due to the increased number of scientific publications, the manual SLR becomes very limited and can be done with a small set of scientific publications. In addition, the SLR process itself is identified as complex, time-consuming, knowledge-intensive, and error-prone because of a lack of adequate technological assistance. Therefore, an automated SLR is needed. This research proposes a new way to automate complex and dynamic SLR processes based on fuzzy reasoning and machine learning techniques, which have been successfully applied for similar problems.
Therefore, this research aims to expand and improve the performance of complex and dynamic SLR processes by offering fuzzy reasoning and a machine learning approach.
Tasks:
1. To analyse existing SLR automation approaches.
2. To analyse the possibilities of applying fuzzy reasoning and machine learning techniques to SLR process automation.
3. To propose expanding existing or creating a new approach of fuzzy reasoning and machine learning-based SLR process automation.
4. To develop a software prototype of the proposed approach and carry out experiments. Based on the obtained results, determine the degree to which the proposed approach and its implementation achieve the defined aim.
Expected main results:
1. A new or expanded way of automating SLR processes based on fuzzy reasoning and machine learning has been developed.
2. The proposed approach of fuzzy reasoning and machine learning-based automation of a complex and dynamic SLR process has been implemented as a software prototype.
The selected candidate will work on the PhD thesis under the supervision of Assoc. Prof. Dr. Diana Kalibatienė. The successful applicant will have to attend scientific conferences, meetings and internships in the other universities.
It is a prerequisite you can be present at and accessible to the institution daily.
For more information
Shortlisted candidates will be invited for an interview. The position may not be opened if no qualified candidate is found. Additional information regarding the post may be obtained from Assoc. Prof. Dr. Diana Kalibatienė, e-mail: diana.kalibatiene@vilniustech.lt
Programme structure
The PhD programme consists of:
· Independent research under supervision;
· Courses for PhD students (approximately 30 ECTS credits);
· Participation in research networks, including placements at other, primarily foreign, research institutions;
· Teaching or another form of knowledge dissemination, which is related to the PhD topic when possible;
· The completion of a PhD thesis.
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