Post Doctoral Researcher Opening distributed computing and networking in School of Computing, National University of Singapore

Post - Doctoral Researcher Ope ning (distributed computing and networking) in School of Computing, N ational University of Singapore (NUS), Republic of Singapore (http://www.comp.nus.edu.sg/)

Background on NUS and Singapore: According to QS World University Rankings 2 012, NUS ranks 9th worldwide in Computer Science and Information Systems. NUS School of Computing has around 80 faculty members and constantly pub lishes in top venues, with some highlight publica tions such as Best Paper in S IGCOM M 20 10 and Best Paper in STOC 2010.

Singapore is an English - speaking develope d country, whose per capita GDP ranks among top 5 in the world. Living c ost is quite reasonable (unless you want to buy a house or a car), and Sing apore has an exceptionally good public transportation system. The crime rate in Singapore is one of the lowest in the world. Details of the Position: An opening is immediately available for the position of Research Fellow (post - doctoral researcher) in the area of distributed computing and networking. The appointee i s expected to work closely with Associate Prof. YU Haifeng (http://www.comp.nus.edu.sg/~yuhf) and his research team on issues related to distribu ted computing and networking.

The most important goal of the research will be t o produce high - impact academic publications in the very best conferences (such as SIGCOMM ) and journals (such as ToN ) in the a rea. The duration is negotiate, but should be at least 1 ye ar (multiple years possible and preferred). Th e starting date is negotiable, and ideally sho uld be no later than the end of 2016. The salary is generous and is internati onally competitive (compared to Europe and US).

Requirements:
- At least a PhD degree from a good university
- Strong publication records
- Fluent in written and spoken English
- Ability and dedication to do world - class research
- Background in distribute d computing and/or networking

How to apply: To apply, please email your CV to YU Haifeng at haifeng@comp.nus.edu.sg. You will be contacted after y our CV has been reviewed. Email haifeng@comp.nus.edu.sg for any inquiries on the position.

Postdoc position in computer systems, VU University Amsterdam

High Performance Distributed Computing Group

The High Performance Distributed Computing group has decades of experience with programming methods for parallel, distributing, and mobile computing. In the past, it produced systems like Orca, MagPIe, Satin, JavaGAT, Ibis, Cuckoo, and SWAN. The group has very strong links to application domains such as machine learning, distributed reasoning, radio astronomy signal processing, digital forensics, e-health, economy, and many others.

An important topic of current research is how to program clusters with many-core accelerators, such as Graphics Processing Units and the Xeon Phi. Another topic is programming environments for distributed mobile applications, such as distributed smartphone-based sensing and Internet-of-Things. Also, combinations of high-performance and mobile computing (e.g., parallel processing on streams of sensor data) are of great interest.

Tasks

The postdoc should do experimental research on programming environments or challenging applications in one of the areas described above. We have a unique distributed experimental testbed (DAS-5) available, consisting of 6 geographically distributed clusters, including a 68-node cluster at the VU with different types of many-cores. In addition, we have a testbed for mobile computing. The work is experimental by nature. We also expect the postdoc to help with education, for example by supervising master projects.

Requirements
Candidates must have a PhD in Computer Science (or a related area) and experience with high performance or mobile computing. The candidate must be proficient in English.

Further particulars

The appointment will be for a period of 1 year. You can find information about our excellent fringe benefits of employment at www.workingatvu.nl such as:

• Remuneration of 8,3% end-of-year bonus and 8% holiday allowance;
• Participation in a solid pension scheme (ABP);
• A minimum of 29 holidays in case of full-time employment;
• A generous commuting allowance (65%) based on public transport.

Salary
The salary will be in accordance with university regulations for academic personnel, and depending on experience, range from a minimum of € 3,168 gross per month up to a maximum of € 3,997 gross per month (salary scale 10) based on a full-time employment.

Information
For additional information please contact:
Prof. dr. ir. Henri Bal
e-mail: h.e.bal@vu.nl
phone: +31 20 59 87733

You may find the following websites useful: 

• Department of Computer Sciences http://www.cs.vu.nl/
• High Performance Distributed Computing Group http://www.cs.vu.nl/en/research/computer-systems/hpdc/index.aspx

Application

Applicants are requested to write a letter in which they describe their abilities and motivation, accompanied by a curriculum vitae and two or three references.

Please send your application to informatica.secretariaat.few@vu.nl and mention the vacancy number in the e-mail header.

Any other correspondence in response to this advertisement will not be dealt with.

Postdoctoral Researcher to work on a project in the area of QoS Optimization in Market-Oriented Cloud Computing

We are seeking a highly motivated Postdoctoral Researcher to work on a project in the area of QoS Optimization in Market-Oriented Cloud Computing. The project is in collaboration with RMIT Australia.

The research project aims to develop a novel and unique framework for a sustainable and efficient cloud service market.  It aims at providing cloud consumers with the best set of tools to outsource tasks to cloud providers that meet their own economic model for costs savings, and QoS requirements over a period of time. The project also aims at empowering cloud providers with a novel framework to advertise their services and taking advantage of the economies of scale to maximize their profit.
This research centers on the development of a novel QoS-based cloud service composition framework for both cloud end-users and cloud service providers. 

The contract is for 2 years and the candidate must be reallocated to Qatar. The position is available immediately and will remain open until filled.

Applicants should have the following qualifications:

• Ph.D. degree in Computer Science in an area close to the scope of the project.
• Strong background in one or more of the following areas: Market-Oriented Cloud Computing, QoS modelling and Optimization, QoS-based cloud service composition, Economic models for Cloud Computing.
• Good publications record demonstrating ability to conduct quality research.
• Strong English communication skills.

Applications will be reviewed immediately and the review process will continue until the position is filled.

Employment benefits include:

• Competitive, tax-free salary
• Housing allowance
• Annual round-trip air tickets for the candidate and his/her dependents
• Educational allowance for candidate’s children, in accordance with QU HR policies
• Public health care and health insurance to candidate and family members
• Annual paid leave, in accordance with QU HR policies

To apply, candidates should email the following to erradi@live.com:

• Curriculum Vitae, including lists of publications, educational background and work experience
• Short research statements (maximum 1 page)
• Names and email addresses of at least 3 references

Qatar University Profile

Qatar University is the premier national institution of higher education in Qatar offering a variety of academic, research and community outreach programs. Qatar University has an international faculty dedicated to the education of its 15,000+ students and to building strong graduate programs and research capabilities with emphasis on addressing national and regional needs and priorities.
The University is located in Doha, Qatar, a vibrant modern city which welcomes visitors and residents from around the globe. The state of Qatar is a small peninsula in the Arabian Gulf, with substantial oil and natural gas reserves. Qatar is one of the wealthiest states in the region and has developed high quality health care and education systems. The country has dedicated 2.8% of its revenue to fund scientific research. The country is bilingual in both Arabic and English. Doha offers all of the modern facilities and services found in the world’s major cities and a safe and high quality life style.

Contact

Phone: 4403 4254
Office:  C07-132  Female Engineering Building
erradi@qu.edu.qa

 

http://faculty.qu.edu.qa/erradi/

 

 
 
 

PhD position in Networks, Simula Research Laboratory AS

Deadline:2016-03-15

About Simula

Simula Research Laboratory AS is a publicly owned research institute located outside Oslo, Norway. We are a multi-cultural organization, employing about 150 individuals from 30 countries. Simula conducts ICT research in the fields of communication technology, scientific computing and software engineering, with the main objective of generating new understanding and creating vital knowledge about fundamental scientific challenges that are of genuine value to society. This is achieved through high quality research, education of graduate students, industry collaboration, technology transfer and commercialization.

Project Description

Centre for Resilient Networks and Applications (CRNA) at Simula focuses on robustness and security of ICT infrastructures. This implies research on networks and applications with the aim of making them resilient with respect to failures and changing environment. The Networks department works on resilience in communication networks and applications from a measurement perspective, through prototyping and through theoretical studies.

We are looking for a PhD student to join our team of senior and junior researchers in the Networks department of the CRNA. The successful candidate will be part of a national project called DOMINOS that aims to investigate, monitor, and improve the resiliency and robustness of the Internet infrastructure in particular and communication networks in general. The project also intends to explore interdependencies between communication networks and other infrastructures like the power grid. We will follow an empirical measurement-driven approach that involves using existing publicly available data sets as well as designing novel measurement tools and techniques.

Responsibilities

The successful candidate is expected to:

• Investigate the resiliency of and the interdependencies in the global routing system
• Contribute to devising inference schemes to identify interdependencies between networks
• Collaborate with the project manager and external collaborators on building a framework for assessing and improving network observability
• Supervise and cooperate with master students

The duration of doctoral fellowship will be 3 years, starting as soon as possible. All PhD students at Simula will be enrolled as PhD students at the University of Oslo Mathematics and Natural Sceince Faculty.
Your Profile
Interested applicants should:

• Hold a Master degree in Computer Science, Electrical Engineering, network science or related fields
• Have a solid background in computer networks
• Basic knowledge of statistics and machine learning is a plus
• Demonstrate excellent level of spoken and written English
•  Be able to start as soon as possible and no later than May 15th
• Possess good interpersonal skills and show willingness to work as part of an international team

Simula Offers

• Excellent opportunities for doing high quality research, as part of a highly competent and motivated team of international researchers.
• Nice office facilities located close to the Oslo fjord and 10 minutes drive from the centre of Oslo, the capital of Norway.
• An informal and including working environment.
• Professional courses and workshops led by international experts on topics such as Communication of Scientific Research, Innovation and Entrepreneurship, and Writing Effective Research Proposals.
• A competitive salary.

Simula strives to achieve a good balance between male and female employees, and women are
particularly encouraged to apply.

Application Requirements

Candidates MUST send their application via the link at the bottom of this page.
Applications sent by e­mail will not be examined.
The application MUST include:

• Curriculum vitae (summarizing education, positions and academic work - scientific publications)
• Master thesis, or abstract of thesis if the thesis itself is unavailable/unfinished
• Cover letter explaining the candidate's background, qualifications and research interests
• Copies of educational certificates, and transcript of records
• Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number).

The application deadline is as soon as possible, but no later than the 15th of March 2016.
Note that all attachments MUST be submitted in PDF format, and with the exception of the CV and the Master thesis, combined into one single PDF-document in the order specified by the list above. To avoid misplacement, please make sure to include your first and last name in the filenames of all documents that you send us.

We are interested in how you first came to learn about this position ­ please let us know in your cover letter.

Applications will be reviewed on a rolling basis until the position is filled.

Contact

For more information, please contact Dr. Ahmed Elmokashfi (ahmed@simula.no, +4747452315).

Postdoc position : Process Analytics for the European Data Science Academy

The European Data Science Academy (EDSA) is a coordination and support action of the H2020-ICT-15-2014 Big data and Open Data Innovation and take-up program. The aim of the EDSA project is to contribute to capacity-building by designing and coordinating a network of European skills centers for big data analytics technologies and business development. TU/e (Eindhoven University of Technology) is one of the nine partners in this program focusing on topics such as process mining and other types of process analytics. In this context we are looking for a Postdoc until January 31st 2018, starting as soon as possible.

Data Science Centre Eindhoven (DSC/e)

The postdoc will join the Architecture of Information Systems (AIS) group at Eindhoven University of Technology (TU/e). AIS is one of the 28 research groups of the Data Science Centre Eindhoven (DSC/e). DSC/e is TU/e’s response to the growing volume and importance of data and the need for data & process scientists (http://www.tue.nl/dsce/). DSC/e is one the largest data science initiatives in the Netherlands and therefore involved in the European Data Science Academy (EDSA). The AIS group is one of the leading groups in the exciting new field of process mining (www.processmining.org). Process mining techniques focus on process discovery (extracting process models from event logs), conformance checking (comparing normative models with the reality recorded in event logs), and extension (extending models based on event logs). The work resulted in the development of the ProM framework that is widely used in industry and serves as a platform for new process mining techniques used by research groups all over the globe. Moreover, many of the techniques developed in the context of ProM have been embedded in commercial tools. See also www.processmining.org.

European Data Science Academy (EDSA)

EDSA aims to deliver the learning tools that are crucially needed in order to educate the data scientists needed across Europe.  Comprised of a consortium of academic and industry institutions with an excellent track record in professional training in Big Data, open data, and business development; and with strong ties to a wide range of stakeholders in the global data economy, EDSA will implement a cross-platform, multilingual data science curricula which will play a major role in the development of the next generation of European data practitioners. To meet this ambitious goal, the project will constantly monitor trends and developments in the European industrial landscape and worldwide, and deliver learning resources and professional training that meets the present and future demands of data value chain actors across countries and vertical sectors. This includes demand analysis, data science curricula, training delivery and learning analytics. EDSA will provide deployable educational material for data scientists and data workers and thousands of European data professionals trained in state-of-the-art data analytics technologies and capable of (co)operating in cross-border, cross-lingual and cross-sector European data supply chains. TU/e will play an important role in the development of learning analytics based on process mining techniques. Specifically, we will monitor study behavior in detail (with careful consideration of privacy issues) and provide insights into the actual learning experience. All events captured (e.g., watching videos or making online assignments) will be stored in a “process cube”, i.e., a data warehouse holding learning-related events and having dimensions based on student attributes (age, experience, gender, nationality), deployment form, and other course characteristics. The process cube will be used to analyze differences between courses and students, e.g., create process models showing differences between students that pass and those that fail. Next to using process mining for learning analytics, the postdoc will be involved in the development of curricula and learning resources focusing on the interplay between process science and data science. Note for example the MOOC Process Mining Data Science in Action (https://www.coursera.org/course/procmin). The MOOC but also the video lectures at TU/e will be analyzed using process mining techniques.  


The postdoc will join the Architecture of Information Systems (AIS) group at Eindhoven University of Technology and focus on the interplay of process mining and data science education. The appointment will be from ‘as soon as possible’, until January 31st 2018.

Requirements

We are looking for candidates that meet the following requirements:

•     a solid background in Computer Science or Data Science (demonstrated by Master and PhD degrees);
•     a relevant PhD is expected (ideal candidates have a strong background in process/data mining and an interest in learning analytics);
•     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).

Conditions of employment

We offer:

•     a full-time temporary appointment for a period of 36 months;
•     salary in accordance with CAO of the Dutch universities;
•     support for your personal development and career planning including courses, summer schools, conference visits etc.;
•     a broad package of fringe benefits (e.g. excellent technical infrastructure, child daycare, and excellent sports facilities).

Information and Application

More information:

The full vacancy, including application form, is available at http://jobs.tue.nl/en/vacancy/postdoc-process-analytics-for-the-european-data-science-academy-254397.html

More information about this position contact dr.ir. Joos Buijs (Assistant Professor), e-mail: j.c.a.m.buijs@tue.nl or by telephone: +31 40 247 3661.
More information about the employment conditions contact drs. Charl Kuiters (HR advisor), e-mail: pzwin@tue.nl or by telephone: +31 40 247 2321.

The application should consist of the following parts:

Cover letter explaining your motivation and qualifications for the position (the letter should show an understanding of process mining and the work done within AIS, see websites such as www.processmining.org and the book "Process Mining: Discovery, Conformance and Enhancement of Business Processes");
    Detailed Curriculum Vitae;
    List of courses taken at the Bachelor and Master level including marks;
    List of publications and software artifacts developed;
    Pointer to a copy of the PhD thesis and key publications;
    Names of at least three referees.

Please apply through this website.
Applications via e-mail will not be accepted!

Phd Research Fellowship On Querying Big Data ,The Norwegian University Of Science And Technology (Ntnu)

PHD RESEARCH FELLOWSHIP ON QUERYING BIG DATA AT THE NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY (NTNU)

One fully-funded PhD research fellowship is offered in the ExiBiDa project (https://www.ntnu.edu/idi/exibida) in the Department of Computer and Information Science (http://www.ntnu.edu/idi) at NTNU.

In ExiBiDa, we will focus on exploratory analysis and querying of Big Data, and develop frameworks and scalable techniques for  supporting such analytical queries. In particular, the PhD candidate will work with challenges related to efficient algorithms and index structures for processing Big Data, within one of the following topics:

1.    Databases on modern hardware (multicore, GPU, NVRAM, etc.)
2.    Efficient query processing on Big Data frameworks (parallel and/or distributed query processing)
3.    Query processing on streaming data
4.    Querying knowledge graphs

Qualifications: A master's degree in Computer and Information Science or equivalent with very good results is required. A solid knowledge of database systems and algorithms and an ability/desire to publish in top  database conferences (VLDB, SIGMOD, ICDE, EDBT, CIKM) are essential.

Since Trondheim is a bilingual city where almost everybody speaks and understands English fluently, candidates need not be afraid of a language barrier. The working language of the research group is
English.

For more information, please contact Prof. Kjetil Nørvåg (noervaag at idi.ntnu.no), http://www.ntnu.edu/employees/noervaag

For detailed information about the positions and application procedure,
please see: https://www.jobbnorge.no/ledige-stillinger/stilling/122205/phd-candidate-within-querying-big-data

Closing date:  15 of March, 2016

PhD scholarship on deep learning and constraint reasoning, France

PhD subject: Deep learning methods coupled with constraint-based reasoning for object recognition in remote sensing data Application to the detection of the Babacu palm tree in Amazonia

Supervisor
Carmen Gervet (Université de Montpellier)
Co-supervisors
Morgan Mangeas (IRD), Samira El-Yacoubi (Université de Perpignan)
Contact
Carmen Gervet carmen.gervet@umontpellier.fr

TOPIC. The most common approaches for object identification within satellite images are based on a pixel analysis, or image segmentation techniques, using expert information or GIS. Machine learning techniques have been successfully  used when the images are enriched with GIS (Huang et al., 1997).

This thesis considers a novel approach based on convolutional neural networks, enriched with structuring methods such as ontologies and constraints generation. Convolutional neural networks have brought a spark in the learning power of neural networks in the past five years, as a deep learning method for efficient classification using a substantial volume of data (1 million of images for thousand classes) (Krizhevsky et al., 2012). Their usage for remote sensing data seems obvious, even though novel to this date. In a context of remote sensing, the images are complex because they are produced by more and more refined spatial and spectral resolutions, and obtained using many complementary sensors.


This thesis has two main objectives:

•    To generate a set-based constraint model that will allow to reduce the search space to be explored (Gervet et Van Hentenryck, 2006). The resulting model will be used to adapt the core architecture of convolutional networks in order to take into account the specific constraints relative to satellite imaging: (i) multiple resolutions (spatial, spectral and temporal), (ii) multiple types of sensors (radar, lidar, optical), (iii) radiometric noises, (iv) high heterogeneity of the observed environment, (v) handling of shadows, clouds, reliefs. A particular attention will be given to the pre-processing that can improve the recognition and the concepts of sensitivity to noise within image used and the robustness of the convergence corresponding to the learning process.

•    To better understand the results by analyzing the mathematical and statistical properties of the parameters found. To do so, ontological models using set constraints will be developed to structure and try to explain the learning process. The idea is to enter the black box of the convolutional network, by seeking to extract its structure and the connections reached, once the learning process completed.
This work will benefit from numerous data, from different projects within the research centre ESPACE- DEV (Maison de la télédétection in Montpellier), applied to different fields such as evolution of land usage and monitoring of land degradation, or the detection of the palm trees in Brazil. A result of digitalization made by human experts can be used as learning basis. Finally, the developed algorithms will be implemented in an automatic processing chain (based on OTB and Python) in order to make available cartography from environmental areas through