Post-Doc postion on Machine-Learning and Big Data Engineering (1.0 fte ) (V32.3920)

Post-Doc postion on Machine-Learning and Big Data Engineering (1.0 fte )

Position
(Post-doctoral) Researcher
Department(s)
Department of Mathematics & Computer Science
FTE
1,0
Date off
31/07/2019
Reference number
V32.3920

Job description

The goal of this project is to develop and evaluate machine-learning campaigns as well as big data architectures that continuously analyze software-defined infrastructures, their qualities, code smells, qualities as well as runtime adaptation possibilities in the scope of DevOps continuous evolution. The Post-Docs will contribute with an advisory, research dissemination, teaching, and mentoring role during the exploration and improvement of state-of-the-art machine- and deep-learning approaches and develop prototypes for the afore-mentioned analysis in the context of sound Empirical Software and Data Engineering research. 

The to-be-developed approaches and algorithms will contribute to high-relevance/high-impact research in the context of two EU H2020 Projects focused on the afore-mentioned topics and most notably, serverless computing. More specifically, one of the two Post-Docs will be actively involved in the EU H2020 RADON project with a co-supervisory role over a Ph.D. student; the post-doc will aid in the envisioning, prototyping, evaluation and dissemination of Defect Prediction approaches specifically designed for infrastructure code. In parallel, the second post-doc will be involved in the EU H2020 SODALITE project with a co-supervisory role over a Ph.D. student; together they will help envision, prototype, and evaluate design patterns and code smells detection facilities for infrastructure code as well as automated code refactoring mechanisms for smart service orchestration.

The applications will also be developed by industrial commercial partners in the scope of the afore-mentioned H2020 actions and will include additional functionality providing the user with further industrial data and information from the value-generating industrial context.

The project is a collaboration of the Jheronimus Academy of Data Science (JADS), 's-Hertogenbosch (campus Mariënburg), Tilburg University (TiU), Eindhoven University of Technology (TU/e) and the commercial, industrial and academic partners part of the actions above. 

Profile
The research will be conducted under supervision of Prof. Dr. Willem-Jan van den Heuvel and Dr. Damian A. Tamburri. The students are expected to deliver both long-term results (understanding of machine learning in quality evaluation of software-defined infrastructures) and mid-term results (algorithms, approaches, high-impact/high-relevance papers, and best practices).

The successful candidate is expected to:

  • Perform scientific research in the domain described;
  • Develop software that implements the algorithms described;
  • Present results at (international) conferences;
  • Publish results in scientific journals;

Participate in activities of the group, mainly in 's-Hertogenbosch but sometimes also in Eindhoven or Tilburg or at one of the commercial partners in several locations in Europe.
 

Job requirements

Job qualifications
Candidates should:

  • Have a MSc. in Mathematics, Statistics, Computer Science, Computer Engineering, AI or a related discipline;
  • Have a strong interest in machine-learning and deep-learning;
  • Have excellent programming skills and be highly motivated, be rigorous and disciplined when developing algorithms and software according to high quality standards;
  • Have good technical understanding of the statistical models used in data science and machine learning;
  • Have knowledge of, or a willingness to familiarize themselves with, current research into machine learning for software engineering quality evaluation;
  • Have a commitment to develop algorithms that analyze Big Data from software-defined infrastructures as well as Big Code;
  • Be a fast learner, autonomous and creative, show dedication and be hard working;
  • Possess good communication capabilities and be an efficient team worker;
  • Be fluent in English, both spoken and written.

Conditions of employment

The Post-Doc will be employed at Tilburg or TU/e University.
We offer:

  • A full-time position.
  • The selected candidate will start with a contract for one year, concluded by an evaluation after approximately 10 months. Upon a positive outcome of the first-year evaluation, the candidate will be offered an employment contract for an additional year (at least, based on performance);
  • A minimum gross salary of € 3.475,- per month;
  • A holiday allowance of 8% and an end-of-year bonus of 8.3% (annually);
  • Researchers from outside the Netherlands may qualify for a tax-free allowance equal to 30% of their taxable salary (the 30% tax regulation). The University will apply for such an allowance on their behalf;
  • Assistance in finding accommodation (for foreign employees);
  • The opportunity to perform cutting edge research in a large-scale joint data science project involving TiU, TU/e, JADS and a commercial partner and bringing together expertise of several senior researchers;
  • Support for your personal development and career planning including participation in courses, summer schools, conference visits, research visits to other institutes (both academic and industrial), etc.;
  • A broad package of fringe benefits (including excellent technical infrastructure, savings schemes and excellent sport facilities).

Information and application

For more information about the project, please contact prof.dr. W.J.A.M. van den Heuvel, email: w.j.a.m.v.d.heuvel[at]jads.nl). Candidates are asked to provide a motivation letter and a detailed CV. ​

You can apply via the apply now button on this page. Mind that you will be redirected to the website of Tilburg University. Applications via the website of the University of Eindhoven cannot be taken into consideration. ​​

The vacancies will be open until we have found suitable candidates for both positions! If you are an interesting candidate we will invite you for an interview to assess whether we can be off value to each other.