PhD position in Paris Saclay Univ, Iterative and Expressive Querying for Big Data Series

PhD position in Paris Saclay Univ Title: Iterative and Expressive Querying for Big Data Series Research Areas: Data Management Systems/Databases, Interactive Visualization, Human-Computer Interaction Summary: 

Domains such as astronomy, and genome sequencing, are currently collecting a staggering amount of data, a significant percentage of which is in the form of data series. To make sense of it, scientists need to interactively explore them, by formulating hypotheses and progressively refining them. Our goal is to add iterative and expressive query mechanisms to big data-series collections. We propose novel interaction and visualization techniques for data series exploration and analysis, and focus on their scalability to multi-terabyte data-series collections. To this end, the thesis will develop interactive tools that allow analysts to express vagueness in their queries and then refine them in an iterative manner. The thesis will also introduce techniques for visualizing high-cardinality query results. Existing data-series indexing algorithms will need to be revised to accommodate the above requirements. Requirements: 

Masters (or equivalent) degree in databases/data management systems or related field, fluency in written and spoken English, solid programming skills. Any background in visualization and human-computer interaction or UI development experience is a plus. The candidate should be enthusiastic about research. Knowledge of French is not required. Coordinators: 

Themis Palpanas, Paris-Descartes University http://www.mi.parisdescartes.fr/~themisp Anastasia Bezerianos, University of Paris-Sud, Inria / Paris-Saclay https://www.lri.fr/~anab/ Starting Date and Funding: 

The thesis is expected to start in October 2016. The duration of a Ph.D. thesis in France is 3 years (maximum 4 years). Full funding is provided, including expenses for international conferences and other major research events.

 Application Process: Contact the thesis coordinators (see above) by April 20, 2016 by including an updated CV and a letter of interest. 

Work Environment:

The work will be conducted between the Paris Descartes University, located in the heart of Paris, and Inria located at the campus of Paris-Saclay, one of the largest research and business clusters in Europe. The diNo team (Paris Descartes University) directed by Themis Palpanas has world-class expertise on problems related to data series management, indexing, and analysis. It has developed the current state of the art data series indexes, experimentally demonstrating scalability to dataset sizes in excess of 1 billion data series, which is 2-3 orders of magnitude more than previous approaches. The team is applying these techniques to real-world problems, and has ongoing collaborations in this area with neuroscientists (Paris Descartes University), astrophysicists (Paris Diderot University), and Facebook. The HCC team (Paris-Saclay) is part of the DigiScope Equipex project on the use of connected, large display platforms for collaborative analysis of large amounts of information. Anastasia Bezerianos has several international research collaborations related to large data visualization and interaction that have led to publications in the top HCI and visualization venues. These include works on visual perception and graphical chart understanding, data exploration, uncertainty visualization, and temporal visualization and understanding. Theophanis Tsandilas (https://www.lri.fr/~fanis/) has a long experience on sketch-based interfaces, expressive graphical representations, and creativity-support tools.

Fully-funded PhD position on querying Big Data at Norwegian Univ. of Science and Technology

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).

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:  17th of April, 2016

Postdoctoral Researcher Positions on Big Data ​Management & ​Machine Learning, DBWeb Team at Telecom ParisTech

Postdoctoral Researcher Positions on Big Data ​Management & ​Machine Learning

The DBWeb Team at Telecom ParisTech is seeking postdoctoral fellows to work on recent exciting challenges on machine learning​ for ​Big Data ​and the Internet of  Things. The appointment would be for one year, with the possibility of extension to two years. The research will be focused on massive data management and machine learning, with applications ​in several domains (business analytics,​ ​​​smart cities, cybersecurity, etc.).

Telecom ParisTech is an engineering school in Paris​, and one of the leading ​'Grande​s​Ecole​​s'​ in France. It was founded in 1878, and prides itself to have invented ​in 1904 ​the word 'telecommunication​'​. The ​'Grandes Ecoles' are the more competitive variant of universities in the ​French​ ​ ​education system, with student admission ratios of around 5%-10%.

​​Telecom ParisTech is located right in the center of Paris, the capital of France.

Requirements

Prospective applicants should have a recent Ph.D. degree in the following areas: Computer Science/Engineering, Computational Mathematics, or Statistics, and a sound publication record.

Applications

Interested applicants should send by email:

• a cover letter including a brief presentation of their academic record, the motivation and the skills of the candidate
• a full CV
• a list of at least 2 academic/industrial references (names and contact information only, not the actual letters)

The above should be e-mailed in a compressed file named after your surname

 (i.e., .zip) to albert.bifet@telecom-paristech.fr

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/

 

 
 
 

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