In the context of the 3TU.BSR "Big Software on the Run" research program we are 
looking for 6 PhDs and 3 Postdocs interested in Software Analytics and Data 
Science.
Context
Millions of lines of code - written in different languages by different people 
at different times, and operating on a variety of platforms - drive the systems 
performing key processes in our society. The resulting software needs to evolve 
and can no longer be controlled a priori as is illustrated by a range of 
software problems. The 3TU.BSR research program will develop novel techniques 
and tools to analyze software systems in vivo - making it possible to visualize 
behavior, create models, check conformance, predict problems, and recommend 
corrective actions. To deal with Big Software on the Run (BSR), we propose to 
shift the main focus from a priori software design to a posteriori software 
analytics thereby exploiting the large amounts of event data generated by 
today's systems. The core idea is to study software systems in vivo, i.e., at 
runtime and in their natural habitat. We would like to understand the actual 
(desired or undesired) behavior of software. Running software needs to adapt to 
evolving and diverging environments and requirements. This forces us to 
consider software artifacts as "living organisms operating in a changing 
ecosystem". This paradigm shift requires new forms of empirical investigation 
that go far beyond the common practice of collecting error messages and 
providing software updates.

Project
The project will run for a period of four years and is supported by the three 
Dutch technical universities (Eindhoven University of Technology, TU Delft, and 
University of Twente). It was initiated by 3TU.NIRICT, the Netherlands 
Institute for Research on ICT, which comprises all ICT research of the three 
universities of technology in the Netherlands. The PhD positions will run for 4 
years. The three postdocs will be appointed for 2-3 years.

The following chairs/groups are involved:

*        The Architecture of Information Systems (AIS) group at Eindhoven 
University of Technology (Van der Aalst).

*        The Visualization (VIS) group at Eindhoven University of Technology 
(Van Wijk).

*        The Software Engineering Research Group (SERG) at Delft University of 
Technology (Van Deursen)

*        The Cybersecurity Group (CY) at Delft University of Technology 
(Lagendijk)

*        The Formal Methods and Tools (FMT) at University of Twente (Van de Pol 
& Huisman)

Interested PhD candidates are requested to apply on a specific PhD position 
(see details below):

1.      Automatically Discovering Behavioral Software Models from Software 
Event Data (Van der Aalst & Van Deursen) at Eindhoven University of Technology

2.      Model-based Visualization of Software Event Data (Van Wijk & Huisman) 
at Eindhoven University of Technology

3.      Exceptional Patterns (Van Deursen & Van Wijk) at TU Delft

4.      Monitoring Concurrent Software (Huisman & Lagendijk) at University of 
Twente

5.      Privacy Preserving On-line Conformance Checking (Lagendijk & Van de 
Pol) at TU Delft

6.      Parallel Checking and Prediction (Van de Pol & Van der Aalst) at 
University of Twente
Moreover, there will be three postdoc positions:

1.      A postdoc related to PhD projects 1 & 2 at Eindhoven University of 
Technology

2.      A postdoc related to PhD projects 3 & 5 at TU Delft

3.      A postdoc related to PhD projects 4 & 6 at University of Twente

Requirements
We are looking for candidates that meet the following requirements:

*        a solid background in Computer Science, Data Science, or Software 
Science (demonstrated by a relevant Master);

*        for the postdoc  positions a relevant PhD is expected;

*        candidates from non-Dutch or non-English speaking countries should be 
prepared to prove their English language skills;

*        good communicative skills in English, both in speaking and in writing;

*        candidates are expected to realize research ideas in terms of 
prototype software, so software development skills are needed.
Note that we are looking for candidates that really want to make a difference 
and like to work on things that have a high practical relevance while having 
the ambition to compete at an international scientific level (i.e., present at 
top conferences and in top journals).

Appointment and salary
PhDs and postdocs will be employed by the respective university using the 
standard  VSNU conditions for Dutch universities.  See  for more information:

*      
http://w3.tue.nl/en/services/dpo/conditions_of_employment/tue_conditions_of_employment

*      http://www.utwente.nl/hr/en/terms-of-employment/

*      
http://www.tudelft.nl/en/about-tu-delft/working-at-tu-delft/tu-delft-as-employer/

How to apply?
Please apply for the position you are interested in. Each position has a 
contact person and a pointer to a website and e-mail address to actually apply.

PhD 1: Automatically Discovering Behavioral Software Models from Software Event 
Data (Van der Aalst & Van Deursen)
Process models and user interface workflows underlie the functional 
specification of almost every substantial software system. However, these are 
often left implicit or are not kept consistent with the actual software 
development. When the system is utilized, user interaction with the system can 
be recorded in event logs. After applying process mining methods to logs, we 
can derive process and user interface workflow models. These models provide 
insights regarding the real usage of the software and can enable usability 
improvements and software redesign. In this project, we aim to develop process 
discovery techniques specific for software. How can domain knowledge and 
software structure be exploited while mining? How to discover software patterns 
and anti-patterns?

*        More information about this position contact Wil van der Aalst 
(http://wwwis.win.tue.nl/~wvdaalst/).

*        For more information about the employment conditions contact Charl 
Kuiters HR advisor, e-mail: [email protected]<mailto:[email protected]>.

*        You can apply by using the following link: 
http://jobs.tue.nl/en/vacancy/phd-discovering-behavioral-software-models-from-software-event-data-206118.html
 or visit http://jobs.tue.nl/en/vacancies.html and choose Department of 
Mathematics and Computer Science and click 'search' to find this vacancy 
(V32.2142).


PhD 2: Model-based Visualization of Software Event Data (Van Wijk & Huisman)
Visualization can be a powerful means for understanding large and complex data 
sets, such as the huge event streams produced by running software systems. 
During explorative analysis experts have to be enabled to see what patterns 
occur, during monitoring anomalous events and patterns have to be detected, 
where in both cases we can exploit the unique capabilities of the human visual 
system. However, simply showing events as a sequence of items will fall short 
because of lack of scalability. The challenge is to enable users to specify 
what they are interested in, and to show only a limited subset of the data, 
using filtering, aggregation, and abstraction. We propose to enable users to 
define models for this, ranging from simple range filters to process models. We 
will study which (combinations of) models are most appropriate here, such that 
occurrences of events, temporal and logical patterns,  and the relations 
between occurrences and attributes of events can be detected, and to facilitate 
analysts to define and check hypotheses on patterns.

*        More information about this position contact Jack van Wijk 
(http://www.win.tue.nl/~vanwijk/).

*        For more information about the employment conditions contact Charl 
Kuiters HR advisor, e-mail: [email protected]<mailto:[email protected]>.

*        You can apply by using the following link: 
http://jobs.tue.nl/en/vacancy/phd-modelbased-visualization-of-software-event-data-206124.html
 or visit http://jobs.tue.nl/en/vacancies.html and choose Department of 
Mathematics and Computer Science and click 'search' to find this vacancy 
(V32.2143).




PhD 3: Exceptional Patterns (Van Deursen & Van Wijk)
A particularly challenging phenomenon in software development are 'exceptions'. 
Most programming is focused on 'good weather behavior', in which the system 
works under normal circumstances. Actual deployment however, often takes place 
in a changing or unexpected environment. This may lead to exceptions being 
raised by the application, which should be handled by the application. 
Unfortunately, predicting such exceptional circumstances is often impossible. 
Consequently, developers have difficulty adequately handling such exceptions. 
Some exceptions are simply swallowed by the applications, others are properly 
logged, and yet other may lead to unpredictable behavior. To resolve this, we 
propose to analyze log files for 'exceptional patterns' -- patterns that hint 
at the presence of exceptions. To find such patterns, we propose to use 
visualization techniques applied to log data and stack traces. Furthermore, we 
will investigate ways to predict future occurrences of exceptions, and 
recommendations on how to improve exception handling in the code base.

*        More information about this position contact Arie van Deursen 
(http://www.st.ewi.tudelft.nl/~arie/).

*        More information on how to apply will follow via 
http://www.tudelft.nl/en/about-tu-delft/working-at-tu-delft/jobs/academic-jobs/.



PhD 4: Monitoring Concurrent Software (Huisman & Lagendijk)
The goal is to develop a monitoring system for concurrent software. Making 
monitoring transparent is the big challenge: monitoring should not affect 
program behavior. A general-purpose approach will be designed, based on local 
annotations and global properties. Runtime monitoring is essential to check 
conformance of concurrent software during deployment. At the same time, runtime 
monitoring provides insight in low-level software events, generating a 
continuous data stream of events that feeds discovery. With process mining and 
visualization technology in Eindhoven, we will explore the scope of concurrent 
software monitoring.

*        More information about this position: see 
http://fmt.cs.utwente.nl/vacancies/ or contact Marieke Huisman 
(http://fmt.cs.utwente.nl/~marieke/ ).

*        More information on the terms of employment: 
http://www.utwente.nl/hr/en/terms-of-employment/ or contact Marlies Oude Bos, 
HR advisor, e-mail: [email protected]<mailto:[email protected]>.

*        You can apply directly using the following link: 
http://www.utwente.nl/vacatures/en/.

PhD 5: Privacy Preserving On-line Conformance Checking (Lagendijk & Van de Pol)
Privacy enhancing techniques have been applied dominantly to data analysis 
problems (such as pattern recognition) and multimedia algorithms (such as 
recommendation engines). The goal of privacy preserving on-line conformance 
checking is to research the problem of privacy and security protection in 
software engineering for the first time. The central problem is that 
conformance checking algorithms may need to operate on event data that is 
sensitive in some way, for instance, contains user-related information. Such 
data can be anonymized or encrypted for protection, yet this might affect the 
accuracy of the conformance checking procedure. It will therefore be necessary 
to find an acceptable trade-off between the level of protection, the utility of 
the results obtained from the privacy-enhanced version of the conformance 
checking algorithm, and the additional computational overhead introduced by the 
anonymization or encryption process.

*        More information about this position contact Inald Lagendijk 
(http://mmc.tudelft.nl/users/inald-lagendijk).

*        More information on how to apply will follow via 
http://www.tudelft.nl/en/about-tu-delft/working-at-tu-delft/jobs/academic-jobs/.




PhD 6: Parallel Checking and Prediction (Van de Pol & Van der Aalst)
Based on the models discovered by online observations (Track 1), the goal of 
this research project is to develop scalable technology for predicting future 
system behavior (Track 3). Assuming that the  system's components will behave 
similar to the process models learnt so far, (quantitative) model checking  
techniques will be applied to explore possible runs and interactions of the 
integrated system. In order to support online recommendations (Track 4), the 
model checking results should be available nearly instantaneously. This calls 
for parallel, scalable algorithms that will be run on local and national cloud 
infrastructure.

*        More information about this position: see 
http://fmt.cs.utwente.nl/vacancies/ or contact Jaco van de Pol 
(http://fmt.cs.utwente.nl/~vdpol/).

*        More information on the terms of employment: 
http://www.utwente.nl/hr/en/terms-of-employment/ or contact Marlies Oude Bos, 
HR advisor, e-mail: [email protected]<mailto:[email protected]>.

*        You can apply directly using the following link: 
http://www.utwente.nl/vacatures/en/.



Postdoc 1: Software Analytics and Process Mining (Van der Aalst)
The postdoc will be involved in the supervision of the PhDs based at Eindhoven 
University of Technology (PhD positions 1 & 2). Moreover, the postdoc will also 
run the Eindhoven side of the 3TU.BSR "Big Software on the Run" research 
program. This also includes making sure that software and application efforts 
are integrated and coordinated between the different subprojects.

*        More information about this position contact Wil van der Aalst 
(http://wwwis.win.tue.nl/~wvdaalst/).

*        For more information about the employment conditions contact Charl 
Kuiters HR advisor, e-mail: [email protected]<mailto:[email protected]>.

*        You can apply by using the following link: 
http://jobs.tue.nl/nl/vacature/postdoc-software-analytics-and-process-mining-206130.html
 or visit http://jobs.tue.nl/en/vacancies.html, choose Department of 
Mathematics and Computer Science and click 'search' to find this vacancy 
(V32.2144).


Postdoc 2 (TUD): Information will follow later.


Postdoc 3: Monitoring, Testing and Conformance Checking (Van de Pol)
This postdoc will investigate the frontier between model-based testing, runtime 
monitoring and conformance checking. The goal is to evaluate and improve 
test-generation techniques based on massive data gathered from online 
monitoring and the software development process, in collaboration with TU Delft 
(van Deursen) and TU Eindhoven (van der Aalst).
The postdoc will be involved in the supervision of the PhDs based at the 
University of Twente (PhD positions 4 & 6). Moreover, the postdoc will also run 
the Twente side of the 3TU.BSR "Big Software on the Run" research program. This 
includes ensuring that software and application efforts are integrated and 
coordinated between the different subprojects.

*        More information about this position: see 
http://fmt.cs.utwente.nl/vacancies/ or contact Jaco van de Pol 
(http://fmt.cs.utwente.nl/~vdpol/).

*        More information on the terms of employment: 
http://www.utwente.nl/hr/en/terms-of-employment/ or contact Marlies Oude Bos, 
HR advisor, e-mail: [email protected]<mailto:[email protected]>.

*        You can apply directly using the following link: 
http://www.utwente.nl/vacatures/en/.


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