Career Opportunities in Network Security

Career Opportunities

We require 5 engineers to get free training on network securrity. the lab is based in bangalore. The course starts on 1st december. After the successfu training jobs are assured wih a high profile MNC. The  skills expected are linux, basic networking and strong english speaking skills. Please contact Manjusha at 9900235976. Please respond as soon as possible. you can also send email at edu@seria.in

Job: Research Associate in UCL Machine Reading Group

Applications are invited for a Postdoctoral Research Associate in Statistical Natural Language Processing and Machine Learning to work with Dr Sebastian Riedel (UCL Computer Science).

The overarching goal of this project is to develop reading and reasoning machines that perform tasks which require a deeper understanding of language, such as question answering, automatic fact checking, and passing multiple-choice science exams. Towards this end we will develop methods that integrate scalable and robust matrix/tensor factorization models [1] (and possibly deeper latent models) with expressive symbolic approaches [2].

The associate will be part of the UCL Machine Reading lab in the Computer Science department, a rapidly-expanding group located in the Bloomsbury campus in central London. The lab is affiliated with the Centre for Computational Statistics and Machine Learning (bringing together CS, the Gatsby unit and Statistics department). Several close links to relevant industry in London exists (BBC, Google, Microsoft, Google Deepmind), as well as to the vibrant academic NLP scene in the South England area.  

The ideal candidate will have:

• a PhD in Computer Science or Statistics with a focus in machine learning and/or natural language processing,
• presented publications at top NLP/ML conferences (e.g., ACL, NAACL, EMNLP, ICML, NIPS),
• experience with matrix and tensor factorization, graphical models and neural networks,

• strong coding skills and
• the ability to work independently and supervise students.

Application Closing Date: 15 Dec 2014

Start Date: January 2015 at the earliest, but there is some flexibility if the perfect candidate needs to start later if necessary.

Duration: the post is funded for 3 years in the first instance.

For more details, and to apply, please follow this link:

https://atsv7.wcn.co.uk/search_engine/jobs.cgi?SID=amNvZGU9MTQ0NDEyMSZ2dF90ZW1wbGF0ZT05NjUmb3duZXI9NTA0MTE3OCZvd25lcnR5cGU9ZmFpciZicmFuZF9pZD0wJmpvYl9yZWZfY29kZT0xNDQ0MTIxJnBvc3RpbmdfY29kZT0yMjQmcmVxc2lnPTE0MTU4MTI3NjEtMmI1NDlkYzZiZDAxMDlmNDJjZTdiYTMzYTY3ZmQwN2UwMTRkZThlZQ==

[1] http://www.riedelcastro.org/publications/details/riedel13relation.html

[2] http://www.riedelcastro.org/publications/details/rocktaschel14low.html

PhD Fellowships at School of Information Studies, Syracuse University

Syracuse University's School of Information Studies welcomes applicants for our doctoral program. Admitted students are assured of at least four year's funding (including summers) along with tuition and other support.

The interdisciplinary nature of our program is visible through the backgrounds of the 40 students currently pursuing their Ph.D.  Students hail from ten countries and a range of academic backgrounds:  communications and other social sciences, business, computer science, library science, information science, and others.   This makes our doctoral program a welcoming and inclusive place for scholars from under-represented populations, something we see as a defining element of our program.

Doctoral students pursue individualized course plans that are tuned to their particular research interests and needs.  This means advising and, more importantly, close working relationships with faculty members is a cornerstone of the Syracuse University iSchool Ph.D. program. This is why it is both residential and full-time.

We celebrate the success of our recent graduates who are taking up tenure-track positions in premier research institutions and exceptional liberal arts colleges, excelling in academic and policy think tanks, and pursuing entrepreneurial success! Current students are earning awards for their publications and dissertation work, continuing a long tradition of such recognition.

For 2015, we are particularly interested in speaking with applicants and seeing applications from those whose interests align with one or more of the following research areas:
+ Text and data mining, Natural Language Processing and Information Retrieval
+ Data science and data analytics
+ Information policy, Internet governance, and telecommunications policy
+ Information technology policy and globalization
+ Librarianship
+ Mobile computing
+ Usability, accessibility, and universal design
+ Data infrastructure and services in support of research
+ Organizational impacts of ICTs (e.g., Citizen Science, FLOSS, Wikipedia, mobile work, distributed scientific collaboration, health IT)
+ Digitally-enabled research methods (e.g., Trace ethnography, socio-computational approaches)
+ Smart grids/energy informatics and Infrastructure studies
+ Information security and privacy (policies, management, and technologies)
+ Social Computing, social media, social networks, and crowdsourcing

You can learn more about the Syracuse iSchool faculty and interests at http://ischool.syr.edu/future/doctoral/research_areas.aspx.

You can learn more about the doctoral program and application (due 3 January, 2014) at http://ischool.syr.edu/future/doctoral/index.aspx.

Please reach out to the program director, Steve Sawyer, at ssawyer@syr.edu, or our doctoral programs manager, Jennifer Barclay, at jabarcla@syr.edu, with questions!

--
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[JOB] Seeking Two postdoctoral positions at Aix Marseille university in multimodal video recommendation

Dear colleagues

Our team is seeking two postdoctoral positions in multimodal video recommendation.

Two postdoc positions at AMU in multimodal video recommendation

Application deadline: 11/31/2014

Description:

The ADNVIDEO project, funded in the frame work of A*MIDEX (http://amidex.univ-amu.fr/en/home), aims at extending multimodal analysis models. It focuses on jointly processing the audio stream, the speech transcript, the image flow, scenes, the characterization of text overlays and user feedback.

Using as starting point the corpus, annotations and approaches developed during the REPERE challenge (http://defi-repere.fr), this project aims at going beyond indexing on a single modality by incorporating information retrieval methods, not only from broadcast television, but more generally on video documents requiring multimodal scene analysis. The novelty here is to combine and correlate information from different sources to enhance the qualification of content. The application for this project relates to the issue of recommendation applied to videos: given a video, the system finds documents (text, image, and video) related to this video, either on the surface level or the meaning level. In particular, the use case considered may have, in terms of technology transfer, significant economic benefits, regarding automatic ad targeting: automatically find the most relevant advertising with respect to the content of a video.

Objectives:

The candidate will participate in the development of a prototype for videos recommendation, leading to a technology transfer towards business:

·       Extraction of multimodal low-level descriptors. These descriptors correspond to speech, image and sound / music.

·       Extraction of multimodal high-level descriptors. These semantic-oriented descriptors are extracted from low-level descriptors.

·       Aggregation of multimodal descriptors to form the multimodal footprint of the video.

·       Matching videos and promotional material.

·       Validation of the video recommendation prototype.

·       Participation to the scientific life of the lab, including paper publication.

The allocation of tasks can be performed depending on the skills of the candidate.

Skills:

For this project, we are looking for two candidates with a PhD degree in the areas of information retrieval, natural language processing, machine learning or video analysis:

·       Strong programming skills (C++, Java, Python…).

·       Desire to produce functioning end-to-end systems, life-scale live demos

·       Scientific rigor

·       Imagination

·       Top notch publications

·       Excellent communication skills

·       Enjoy teamwork

Candidates must presently work outside of France.

Location:

University of Aix-Marseille, LIF (http://www.lif.univ-mrs.fr) and LSIS laboratories (http://www.lsis.org) and the company Kalyzee (http://www.kalyzee.com/).

Contact: sebastien.fournier@lsis.org

Duration: 23 month

Candidates should email a letter of application, a detailed CV including a complete list of publications, and source code showcasing programming skills.

Postdoctoral Research Position in Recommender Systems TU Delft, Netherlands (10 Nov deadline)

Delft University of Technology (TU Delft) is currently recruiting a post-doctoral researcher for a period of two years, to work within the CrowdRec project (crowdrec.eu), devoted to the development and evaluation of next-generation recommender systems that fuse multiple information sources.

The researcher will work closely with the Multimedia Computing Group team, and will:

- Develop algorithms in the area of recommender systems, including context-aware, socially-informed, and crowd-driven approaches.
- Publish in top venues, e.g., ACM RecSys, ACM Multimedia.
- Contribute to the CrowdRec Reference Framework, which publishes reference implementations of developed algorithms.
- Work together with CrowdRec partners around Europe, including Barcelona, Milan, Budapest, to carry out large-scale testing of recommender algorithms.
- Guide students at all levels (Bachelor, Master, and PhD) who are carrying out work in the area of recommender systems and multimedia.
- Contribute to the innovation of new research challenges and the development/organization of community benchmarks.
- Participate in the reporting and analysis of research results, including project meetings, and roadmapping meetings with the CrowdRec External Advisory Board.
- Develop new research areas and project concepts in collaboration with colleagues working on other projects in the Multimedia Computing Group (e.g., in the areas of music, social networks, quality of multimedia experience).

*Requirements*
The successful candidate will have:
- A PhD in a field related to multimedia and/or recommender systems.
- A proven track record of research leading to publications in top venues.
- A background in machine learning.
- Programming skills necessary to participate in the implementation of reference implementations (Java, C++, C# or Python).
- Experience with the organization of international research events, especially research challenges or benchmarks.
- Interest in working closely with companies to carry out large-scale evaluation of recommender systems.
- Interest in or experience with the application of crowdsourcing or gamification techniques in multimedia.

*Conditions of employment*
TU Delft offers an attractive benefits package, including a flexible work week and the option of assembling a customized compensation and benefits package (the 'IKA'). Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. Contract type: Temporary, 2 years

For more information about this position, please contact Martha Larson, phone: +31 (0)15-2787357, e-mail: m.a.larson@tudelft.nl. To apply, please e-mail a detailed CV, publications list and two references along with a letter of application by 10 November 2014 to Mrs. C.J.C.Kohlmann van Noord, Hr-eemcs@tudelft.nl.
When applying for this position, please refer to vacancy number EWI2014-27.

*Delft University of Technology*
Delft University of Technology (TU Delft) is a multifaceted institution offering education and carrying out research in the technical sciences at an internationally recognized level. Education, research and design are strongly oriented towards applicability. TU Delft develops technologies for future generations, focusing on sustainability, safety and economic vitality. At TU Delft you will work in an environment where technical sciences and society converge. TU Delft comprises eight faculties, unique laboratories, research institutes and schools.

*Electrical Engineering, Mathematics and Computer Science (EEMCS)*
The Department of Intelligent Systems (INSY) within the EEMCS faculty conducts research on processing and interpretation of data to address the increasing volume and complexity of data and communication in today's world.

The Multimedia Computing Group within the INSY Department develops algorithms for enriching, accessing, and searching large quantities of data. The focus is on developing systems that are oriented to the needs of users, making possible satisfying, personalized interaction with large collections of multimedia data (e.g., images, video, and music shared online) in real-world contexts (e.g., within social networks). The group combines expertise on multimedia information retrieval, recommender systems, multimedia signal processing, social network analysis, and quality of experience.

Additional information
Martha Larson
+31 (0)15-2787357
m.a.larson@tudelft.nl

Earn your PhD in IR at the U. of Texas at Austin

The University of Texas at Austin invites applications from talented and energetic prospective students wanting to help shape the future of research in Information Retrieval (IR). UT Austin is one of the premier research universities in the US and is located in one of the country's sunniest and most vibrant cities in which to live and work, Austin.

    http://ir.ischool.utexas.edu/gradstudy.html

I have openings in my own lab to fully-support new students interested in research at the intersection of IR and human computation / crowdsourcing:

    http://ir.ischool.utexas.edu/

and we have three other faculty also doing great research in IR:

* Jacek Gwizdka: interactive IR, neuro-modeling of relevance -- http://www.ischool.utexas.edu/~jacekg

* Yan Zhang: medical information seeking -- https://www.ischool.utexas.edu/~yanz

* Byron Wallace: automatic IR for biomedical articles -- http://byron.ischool.utexas.edu

PhD Applications for our School of Information (iSchool), ranked 6th nationally, are due November 15th.

    https://www.ischool.utexas.edu/admissions/phd

While we do not guarantee consideration of late applications, the closer to the deadline an application is received, the greater the likelihood that it will be considered.

If you haven't heard of an iSchool before, read more about them:

    http://ischools.org/about/

The UT Austin School of Information is committed to making a difference in the world by designing information management solutions that are accessible, useful, usable, and sustainable. To increase scientific understanding of the role and impact of information in all human endeavors, we study problems and develop solutions for better information design, management, organization, preservation, and retrieval.

Our curriculum allows individual programs of study to be tailored to meet each student's diverse research interests, preparing all students to become high quality, high-impact researchers in their targeted areas of interest.

I came to the UT Austin iSchool with a PhD in Computer Science and have found it to be a great place to research and study IR.  iSchools have plenty of computing research opportunities (and more) to offer!

In comparison to the iSchool, the CS department tends to have even more applicants, so CS admissions tends to be even more competitive. It's okay to apply to both iSchool and CS programs; each has its own separate admissions process, as well as beautiful new facilities in which to work and study.

http://www.cs.utexas.edu/graduate-program/prospective-students

UT Austin uses a centralized application process, which means I do not get to decide whether or not to accept a given applicant. The admissions committee will review all applications and make a holistic evaluation of each applicant's overall potential for excellence in research.

We look forward to receiving your application and hope you will be able to join us at UT Austin next Fall!

--
Matt Lease
Assistant Professor
School of Information and Department of Computer Science
University of Texas at Austin
Voice: (512) 471-9350 · Fax: (512) 471-3971 · Office: UTA 5.442
http://www.ischool.utexas.edu/~ml
--
Matt Lease
Assistant Professor
School of Information
University of Texas at Austin
Voice: (512) 471-9350 · Fax: (512) 471-3971 · Office: UTA 5.442
http://www.ischool.utexas.edu/~ml