[TYPES/announce] Looking for PhDs and Postdocs in Software Analytics and Data Science for 3TU.BSR "Big Software on the Run" research program
Marieke Huisman
m.huisman at utwente.nl
Mon Feb 9 03:29:20 EST 2015
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 postdocpositions 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 standardVSNU 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/
<http://wwwis.win.tue.nl/%7Ewvdaalst/>).
·For more information about the employment conditions contact Charl
Kuiters HR advisor, e-mail: pzwin at tue.nl <mailto:pzwin at tue.nl>.
·You can apply by using the following link:
http://jobs.tue.nl/en/vacancy/phd-discovering-behavioral-software-models-from-software-event-data-206118.htmlor
visit http://jobs.tue.nl/en/vacancies.htmland 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: pzwin at tue.nl <mailto:pzwin at tue.nl>.
·You can apply by using the following link:
http://jobs.tue.nl/en/vacancy/phd-modelbased-visualization-of-software-event-data-206124.htmlor
visit http://jobs.tue.nl/en/vacancies.htmland 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/
<http://fmt.cs.utwente.nl/%7Emarieke/>).
·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: m.oudebos at utwente.nl <mailto:m.oudebos at utwente.nl>.
·You can apply directly using the following link:
http://tinyurl.com/3TU-BSR-PhD4 <http://tinyurl.com/3TU-BSR-PhD6>
/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/ <http://fmt.cs.utwente.nl/%7Evdpol/>).
·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: m.oudebos at utwente.nl <mailto:m.oudebos at utwente.nl>.
·You can apply directly using the following link:
http://tinyurl.com/3TU-BSR-PhD6.
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/
<http://wwwis.win.tue.nl/%7Ewvdaalst/>).
·For more information about the employment conditions contact Charl
Kuiters HR advisor, e-mail: pzwin at tue.nl <mailto:pzwin at tue.nl>.
·You can apply by using the following link:
http://jobs.tue.nl/nl/vacature/postdoc-software-analytics-and-process-mining-206130.htmlor
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/ <http://fmt.cs.utwente.nl/%7Evdpol/>).
·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: m.oudebos at utwente.nl <mailto:m.oudebos at utwente.nl>.
You can apply directly using the following link:
http://tinyurl.com/3TU-BSR-PD3
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