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What Our People Say
Lero is a great place to work. One of the best aspects of Lero is the wealth of the scientists from a number of different universities it brings together. I especially love the opportunities you get in Lero to work on challenging/state of the art projects and ideas. I also find remarkably rewarding outreach activities we do such as talks and workshops aimed to inspire the next generation and especially females to consider careers in STEM.
I have been working with Lero Since Dec 2015. Lero provides great chances and facilities for researchers to do their research activities. Lero coordinates scientific events to provide networking possibilities for researchers from diverse disciplines, to exchange their knowledge. In Lero, you will find yourself very well-equipped and supported to realize your scientific ambitions.
I visited Lero for three months during my PhD and got really impressed by people, meaningful research, collaboration with industry and resources. So I decided to join permanently as a postdoc 2 years ago, and since then I've been able to confirm all these impressions, and to enjoy the vibrant campus of University of Limerick.
Based at the University of Limerick, Ireland, and affiliated with:
Lero - The Irish Software Research Centre (https://www.lero.ie)
Enable - Research Programme on Smart Communities (https://www.enable-research.ie)
Confirm - Centre for Smart Manufacturing (https://confirm.ie)
The closing date for receipt of applications is 12 noon, Irish Standard Time Wednesday, 1st May 2019.
Further information for applicants and application material is available online from http://www.ul.ie/hrvacancies/
The positions are based in a thriving, creative, multi-displinary software research group (http://spare.lero.ie), with deep and extensive academic collaborations, industrial partners, and a collegial and supportive working environment.
Applicants from a wide variety of backgrounds are welcome, including from software engineering, security engineering, privacy management, digital forensics, mobile and ubiquitous computing, and/or adaptive systems.
Applicants with experience in application areas like smart cities, smart manufacturing, Industrie 4.0/Cyber-Physical Systems, Internet of Things, etc, are also welcome.
Potential applicants are encouraged to contact Prof Bashar Nuseibeh <Bashar.Nuseibeh@lero.ie> for an informal discussion. If possible, please include a CV and a sample publication with your email
Please note that formal applications (online) must include:
- A letter of introduction indicating how you meet the criteria outlined in the Job description.
- A completed online Application Form
Please email email@example.com if you experience any difficulties
Applications are welcome from suitably qualified candidates.
The continuous software engineering paradigm aims to accelerate software development activities by automating the software development process as a whole. With the ever-increasing speed of delivery of new software features in continuous software engineering, automated and preferably intelligent recommendation systems inevitably become possible. To optimize the deployment experience, such artifacts that are powered by artificial intelligent agents can be triggered, for example, when a suspect unit of code is committed into the source code repository. Consequently, an agent can monitor and analyze software practitioners’ activities to profile their development activities and ultimately can personalize suggestions based on captured experiences. Requirements
Qualified Ph.D. students will have fees covered for up to 4 years and a stipend of approximately €16k/annum for the same period, dependent on maintaining progress and engaging with the School structured pathway of accredited modules as appropriate.
Aims and objectives
The goal of this PhD project is twofold: The first goal is to design a software development activity monitoring agent that is equipped with an interception mechanism to identify suspect cases, for example of high complexity or an absence of corresponding test assets. The secondary goal is to improve the agent by adding recommendation skills to address other potential instability perspectives including but not limited to frequency of integration footprint for the integrator, lines of code committed, as well as coupling metrics for newly changed code. Together, these metrics which have up-to-this-point been used infrequently and largely in isolation can be combined in a powerful, intelligent fashion as a type of an intelligent agent that can offer greater confidence in software quality in the automated development and production environments of the future.
Candidates should have completed (or be close to completion of) a master’s degree in Computer Science (or closely related fields such as Informatics) and a background in software engineering with experience in application design and development. A thesis-based research Master’s level degree from a reputed university is helpful. Solid programming (coding and debugging) skills are necessary, and sound knowledge of Python and/or Java is preferable. Familiarity with artificial intelligence and machine learning libraries is appreciated. Good writing skills are expected to publish research manuscripts with the supervisors. We would like to follow a PhD by publication path.
Supervisor: Dr. Murat Yılmaz, School of Computing Dublin City University & Lero, the Irish Software Research Centre, firstname.lastname@example.org
Co-Supervisor: Dr. Paul Clarke, School of Computing Dublin City University & Lero, the Irish Software Research Centre, Paul.M.Clarke@dcu.ie
Inquiries on this project can be made informally to Dr. Murat Yilmaz (email@example.com https://www.computing.dcu.ie/~myilmaz/) with your curriculum vitae, cover letter, transcripts, and GRE/TOEFL/IELTS scores. (TOEFL/IELTS can be waived if you already have a degree from an institution where the language of instruction is English.)
- The ideal candidate will have a PhD in software verification with PhD and postdoctoral experience of a number of the following: formal verification tools used in industry such as Promela/SPIN,TLA+, Frama-C; formal models of concurrency; weak memory models; probabilistic modelling; refactoring code to minimise false positives from static analysis tools; software certification and qualification processes; real-time operating systems; and related topics.
- Send an email to Dr. Andrew Butterfield (Firstname.LastName@scss.tcd.ie) containing:
- Contact details for at least two referees
- Cover letter detailing why you feel you are suited to the position.
- Application Deadline: 12noon (IST) Wednesday 18th September
- Trinity College Dublin is an equal opportunities employer
RTEMS-SMP Qualification is an activity funded by the European Space Agency (ESA) to perform pre-qualification of an upcoming release of the open-source real-time operating system RTEMS (rtems.org). This release provides support for running RTEMS on multi-core systems. It follows on from previous work in this area funded by ESA.
Researchers from Lero, the Irish Software Research Centre are involved in a task that explores the use of formal verification techniques in this qualification process. The task is to deploy formal techniques such as formal modelling, model-checking, and theorem proving, to assist in improving the quality of qualification results in key areas.
Key areas under consideration include: modelling and verifying the multicore scheduling algorithms MrsP and OMIP and key synchronisation primitives; exploring how formal methods can help with test generation, and particularly for assembly code, with coverage analysis; and probabilistic reasoning to work around testing difficulties due to lack of predictability inherent in multi-core systems.
This will require the development and revision of requirements for these algorithms, development of formal models for appropriate formal tools and ways to automate, as far as is practical, the running of those tools.
Two key challenges are: to produce outputs that are suitable for software qualification; while doing this in a way that is acceptable to the open-source community (rtems.org) that maintains the operating system.
The activity is being run by a consortium led by Thales Edisoft (Portugal), with partners Embedded Brains (Germany), Jena Optronik (Germany), CISTER Research Centre, ISEP (Portugal), and Trinity College Dublin (Ireland) as part of Lero, the Irish Software Research Centre.
- Relevant Honours level Engineering / Science degree or similar.
- Masters or PhD degree in a related discipline or industry experience is an advantage.
- Experience in data mining techniques example data pre-processing, data analysis, pattern recognition etc.
- Experience in algorithm development and machine or Deep learning techniques.
Applications closing: Tuesday April 23rd @ 12 noon. All applications must be made online at www.ittralee.ie
We are looking for a highly motivated Research Assistant to join the research team at IMaR @ ITTralee. The successful candidate will work on data analytics and machine learning projects in collaboration with industrial partners and the SFI Lero team. The successful candidate may have the opportunity to lead aspects of the overall project.