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PhD fellow in Declarative Process Mining

Københavns Universitet (KU)

Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD scholarship in Declarative Process Mining commencing 1 May 2021 or as soon as possible thereafter.

Description of the scientific environment
The PhD project will be hosted by the Software, Data, People & Society (SDPS) Section and affiliated to the DIREC research center (DIREC.dk). The SDPS section performs research in software, process, and data management systems, with focus in particular on methods for the development of software systems that closely match the needs of developers, users, and society. The research is often carried out in an interdisciplinary context and in collaboration with industry. In particular, the student will be a member of the Process Modelling and Intelligence (PMI) research group.

Research at the PMI group centers around the concept of processes in all their forms, including but not limited to, business, development, and physical processes. Notable contributions by members of the group include the Dynamic Condition Response (DCR) Graphs process notation, seminal work on declarative and hybrid process discovery, and research into the application of distributed ledger technologies to cross-organizational processes.

More information on the section and research group can be found on their respective websites:


Project description
The PhD will be part of the AI and Blockchains for Complex Business Processes project, which investigates methods and tools that enable industry to develop new efficient solutions for exploiting the huge amount of business data generated by enterprise and blockchain systems. Topics range from techniques for automatic identification of business events, via the development of new rule-based process mining technologies to tools and responsible methods for the use of process insights for business intelligence and transformation.

Your PhD project will focus on the foundations of declarative process mining. You will design and implement algorithms for the automated discovery and enhancement of rule-based processes. In particular, you will build on previous work on discovering DCR Graphs and extend existing algorithms with capabilities to mine data, time, resources, and hierarchy. You will implement these advances as part of the open source DisCoveR miner. In addition, you will research extending the algorithms with novel sources of input data, such as negatives examples, domain knowledge, and manual user-feedback.

As a strong candidate, you should have extensive experience in process mining, traditional machine learning methods, and declarative formal notations, e.g. linear temporal logic and DCR Graphs. During your PhD project, you are expected to both advance the foundations of the field of declarative process mining through basic research and to build actual systems based on novel ideas. The results of the PhD project are expected to be published in top venues in Business Process Management and Machine Learning.

Principal supervisor isAssociate ProfessorTijs Slaats, Department of Computer Science, slaats@di.ku.dk. Co-supervisor is Associate Professor Søren Debois, Department of Computer Science, IT University of Copenhagen.

Job description
The position is available for a 3-year period and your key tasks as a PhD student at SCIENCE are:

  • To manage and carry through your research project
  • Attend PhD courses
  • Write scientific articles and your PhD thesis
  • Teach and disseminate your research
  • To stay at an external research institution for a few months, preferably abroad
  • Work for the department

Formal requirements
Applicants should hold an MSc degree in Computer Science with good results and good English skills. However, for exceptionally strong candidates the position is also available as an integrated MSc and PhD, see below for details.

As criteria for the assessment of your qualifications, emphasis will be laid on previous publications (if any) and your educational background in the relevant areas.

Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

The starting salary is currently at a minimum DKK 330,284 (approx. €44,000) including annual supplement (+ pension up to DKK 53,674). Negotiation for salary supplement is possible.

Integrated MSc and PhD Scheme
The position is also available for candidates who are (or are eligible to be) enrolled at one of the faculty’s master programmes in Computer Science. The duration of the integrated programme depends on the amount of credits that you have passed on your MSc programme. For further information about the study programme please see: www.science.ku.dk/phd, “Study Structures”.

Scholarship and terms of employment for integrated MSc and PhD
PhD grant portions (Ph.D.
SU klip)
In the period up to the completion of the MSc programme (up to three years), the student is entitled to so-called PhD grant portions. The grant portions are financed by the grant donor but not by the Danish State Educational Grant and Loan Scheme Agency (as is the case for the ordinary study grant portions on the BSc and MSc programmes). They are called PhD grant portions because this kind of remuneration is regulated and described in the Executive Order on the State Educational Grant and Loan Scheme in Denmark (SU‐bekendtgørelsen), and because the value of a PhD grant portion corresponds to the value of an ordinary Danish study grant portion. Students are awarded 48 PhD grant portions during the period of their MSc and PhD studies.
48 PhD grant portions at DKK 6,321 each, corresponding to DKK 303,408 (approx. €40,450).

'Duty work'
As a supplement to the PhD grant portions, the student may, in accordance with the collective agreement of the Danish Confederation of Professional Associations (AC), be offered 'duty work'. In the period up to the completion of the MSc programme, students performing 'duty work' are paid by the hour. UCPH has decided to offer students on integrated MSc and PhD schemes 150 hours of 'duty work' per year during Part A of the programme (until two years of the combined programme of study remain). 'Duty work' during Part A if it has a duration of three years: 450 hours at a rate of DKK 219,23 (+ 12.5% holiday pay), corresponding to DKK 110,984 (approx. €14,790)

For further information about Part A please see: https://www.science.ku.dk/phd/studystructure/integratedphd/.

Salary in accordance with the collective agreement with the Danish Confederation of Professional Associations (AC)
In the period after the completion of the MSc programme, the student is employed as a PhD scholar and is remunerated in accordance with the collective agreement with the Danish Confederation of Professional Associations (AC). The scheme is arranged in such a way that students graduate from the MSc programme at a time when there are two years left of the integrated programme. For this reason, the salary must be paid for a period of two years in accordance with the collective agreement with the Danish Confederation of Professional Associations (AC). The amounts specified include a supplement locally agreed upon as well as pension contributions: Salary as a PhD scholar: 24 months at a rate of DKK 31,996 (including pension contributions and supplement), corresponding to DKK 767,918 (approx. €102,380).

Application Procedure
The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include

  • Cover Letter, stating which PhD project you are applying for and detailing your motivation and background for applying for the specific PhD project.
  • A short research proposal. (Max 2 pages.)
  • CV
  • Diploma and transcripts of records (BSc and MSc)
  • Acceptance Letter for the relevant MSc Programme at SCIENCE, if any
  • Other information for consideration, e.g. list of publications (if any),
  • 1-3 reference letters (if any)

Reference letters must be uploaded by the applicant him/herself. The recruiting person must NOT obtain reference letters which content is not known to the applicant him/herself. This is against Danish law.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

The deadline for applications is February 28th, 2021, 23:59 GMT +1.

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee. Afterwards an assessment committee will be appointed to evaluate the selected applications. The applicants will be notified of the composition of the committee and the final selection of a successful candidate will be made by the Head of Department, based on the recommendations of the assessment committee and the interview committee.

The main criterion for selection will be the research potential of the applicant and the above mentioned skills. The successful candidate will then be requested to formally apply for enrolment as a PhD student at the PhD school of Science. You can read more about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.
For specific information about the PhD scholarship, please contact the principal supervisor Associate ProfessorTijs Slaats, Department of Computer Science, slaats@di.ku.dk.

General information about PhD programmes at SCIENCE is available at https://www.science.ku.dk/phd.

Københavns Universitet giver sine knap 10.000 medarbejdere muligheder for at udnytte deres talent fuldt ud i et ambitiøst, uformelt miljø. Vi sikrer traditionsrige og moderne rammer om uddannelser og fri forskning på højt internationalt niveau. Vi søger svar og løsninger på fælles problemer og gør ny viden tilgængelig og nyttig for andre.

Tijs Slaats
E-mail: slaats@di.ku.dk

Ansøgningsfrist: 28-02-2021

Ansættelsesdato: 01-05-2021

Arbejdstid: Fuldtid

Afdeling/Sted: Department of Computer Science

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