2 PhD positions on Fine Grained Dependency Management Delft University of Technology, Faculty Electrical Engineering, Mathematics and Computer Science Netherlands

2 PhD positions on Fine Grained Dependency Management

 

Department/faculty: Faculty Electrical Engineering, Mathematics and Computer Science 


Level: University Graduate 


Working hours: 38-40 hours weekly 


Contract: 4 years 


Salary: 2266 - 2897 euros monthly (full-time basis)

 

Faculty Electrical Engineering, Mathematics and Computer Science

 

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) is known worldwide for its high academic quality and the social relevance of its research programmes. The faculty’s excellent facilities accentuate its international position in teaching and research. Within this interdisciplinary and international setting the faculty employs more than 1100 employees, including about 400 graduate students and about 2100 students. Together they work on a broad range of technical innovations in the fields of sustainable energy, telecommunications, microelectronics, embedded systems, computer and software engineering, interactive multimedia and applied mathematics.

 

The Department Software Technology (ST) is one of the leading Dutch departments in research and academic education in computer science, employing over 150 people. The department ST is responsible for a large part of the curriculum of the bachelor’s and master’s programmes in Computer Science as well as the master’s programme Embedded Systems. The inspiration for its research topics is largely derived from technical ICT problems in industry and society related to large-scale distributed processing, embedded systems, programming productivity, and web-based information analysis.

 

The Software Engineering Research Group (SERG) is part of the department of Software Technology, faculty of Electrical Engineering, Mathematics, and Computer Science, and a member of the research school IPA. The group employs approximately 30 people, comprising full, associate, and assistant professors, lecturers, postdocs, and PhD students. The main research areas for the group include but are not limited to software analytics, software testing, software quality and maintenance, software evolution and search-based software engineering. The involved researchers have developed numerous techniques to make it easier for software developers to (1) understand, (2) maintain and (3) test existing software systems. 

 

Job description

 

A popular form of software reuse is the use of Open-Source Software (OSS) libraries, hosted on centralized code repositories, such as Maven or NPM. The co-evolving network of dependencies and end user applications that results from linking to packages in online repositories is usually refered to as an ecosystem. As recent events, such as the leftpad incident, which led to hundreds of thousands of websites to stop working, and the Equifax data breach, which led to a leak of hundreds of thousands of credit card numbers, have demonstrated, dependencies on networks of external libraries can introduce to projects significant operational and compliance risks as well as difficult to assess security implications.

 

In the proposed project, we aim to rethink what is possible in software reuse, by making package management more intelligent. Specifically, we will develop tools and techniques to:

 

    • increase observability and analyzability of software ecosystems, by exploring dependencies at the function level;

 

    • tackle the problems of security and risk evaluation, license compliance and change impact analysis at an unprecedented level of precision;

 

    • apply those techniques in three widely popular ecosystems (C, Java and Python).

 

The work will be done in the context of the FASTEN project, a recenlty funded H2020 project. The hired PhD students will work within a strong engineering team spread throughout Europe to develop novel architectures, databases and source code analysis techniques that enable method-level tracking of dependencies in real-time.

 

Requirements

 

We are looking for a fully funded, 4 year PhD candidate who can meet the following requirements:

 

    • has (or will obtain before the starting date) an MSc in Computer Science, Software Engineering or a closely related field;

 

    • has strong software development skills as demonstrated through participation in OSS, industrial projects or exceptional research projects;

 

    • is a team player. Working experience within academic or industrial partners is a plus;

 

    • enjoys research and is self-motivated;

 

    • has excellent communication skills in English;

 

    • is able to articulate the subject matter to relevant stakeholders;

 

    • has practical or research experience on any of the following subjects (big plus): functional programming, big data management systems, machine learning, graph processing or static analyis.

 

 

Conditions of employment

 

TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.

 

As a PhD candidate you will be enrolled in the TU Delft Graduate School. TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit www.tudelft.nl/phd for more information.

 

Information and application

 

For more information about this position, please contact Dr. Georgios Gousious, Assistant Professor, e-mail: g.gousios@tudelft.nl

 

For more information on the procedure, please contact Dr.Ir. Karin Reijenga, HR advisor, e-mail: hr-eemcs@tudelft.nl

 

When applying please send your materials before Janury 15, 2019 to hr-eemcs@tudelft.nl stating vacancy number EWI2018-69.

 

The application should consist of the following parts:

 

    • an explanation of the candidate's interest in the proposed research field;

 

    • a Curriculum Vitae;

 

    • copies of diplomas and other relevant certificates;

 

    • a complete list of attended courses and corresponding grades;

 

    • names and contact details of two referees;

 

    • proof of language skills (if applicable);

 

    • a copy of the candidate's master thesis;

 

  • additional information that supports the candidate's application (e.g. publications, links to open source code etc)


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