Certificate course: Creative Movement Therapy (2015)

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1 open PhD position in NLP at the University of Cambridge

Applications are invited for a 3-year PhD studentship at the crossroads of NLP, big data and disease alerting.

Panda Alert: understanding the significance of adverse health event reports using distributed semantic models

*****Important Dates*****
- Deadline for student applications at DREAM CDT: 19th June 2015
- Short listed applicant interviews: week of 22nd June 2015
- Notification of successful applicants by DREAM CDT: 3rd July 2015
- Doctoral course start: October 2015
- Further information about DREAM: http://www.dream-cdt.ac.uk/studying/application/
- Further information about Graduate Admissions at the University of Cambridge: http://www.graduate.study.cam.ac.uk/courses/directory/mmalpdlng  
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With concerns about the rapid spread of new and re-emerging diseases such as Ebola and A(H1N1) influenza there has been increasing attention on human language technologies which can complement traditional information sources by trawling through news and social media data on a Web-scale to find 'the needle in the haystack' that indicates a first adverse health event report.

Potential PhD students with a strong background in Computer Science, Computational Linguistics or Artificial Intelligence are encouraged to apply for this full-time three-year studentship funded by the NERC Centre for Doctoral Training in Data, Risk and Environmental Analytical Methods (DREAM). The studentship is expected to start in the academic year 2015/16. The student will work within an interdisciplinary team of researchers from Computer Science, Computational Linguistics and Public Health in the Panda Alert project which investigates novel methods for health risk alerting using natural language processing, machine learning and distributed semantic representations.
Motivated by the challenges outlined above the student will examine natural language understanding technology within a high performance computing environment. The exact scope of the project is open to discussion and will be shaped by the student's strengths but we anticipate that the successful candidate will develop a novel approach for early health risk alerting that combines the state of the art in natural language processing with aberration detection to achieve high throughput real-time alerting of novel health threats.

The PhD research will be undertaken at the Department of Theoretical and Applied Linguistics (DTAL) at the University of Cambridge. The successful candidate will be integrated into a friendly research-led team that conducts weekly meetings, publishes in top conferences and journals and with extensive inter-disciplinary collaborations. This is a unique opportunity to work at the cutting edge of computational linguistics.

About you: Applicants should hold a 1st class UK Honours Degree or equivalent in subjects such as Computer Science, Artificial intelligence or Computational Linguistics. Good knowledge of English and communication skills are important, as well as a willingness to work in an interdisciplinary environment and with the open-source community to upstream project outputs.

Funding: UK nationals and EU nationals who have been ordinarily resident in the UK for 3 years will receive tuition fees and a maintenance grant from the NERC CDT fund. Other EU nationals will have fees paid. See: http://www.nerc.ac.uk/funding/application/howtoapply/forms/dtg-faq-students/
For further details: To apply in the first instance please contact Nigel Collier by email with a CV to discuss the application as soon as possible and no later than June 15th.
Dr Nigel Collier
Principal Research Associate
Department of Theoretical and Applied Linguistics
University of Cambridge, Cambridge, UK
Email: nhc30@cam.ac.uk

Supervisory panel: Cambridge Dr Nigel Collier; Dr Anna Korhonen   Industrial partner Joint Research Centre of the European Commission (JRC EC)

Open position: PhD Student - University of Innsbruck/STI Innsbruck

PhD Student - University position

Leopold Franzens University of Innsbruck & Semantic Technology Institute Innsbruck, Austria.

STI Innsbruck (www.sti-innsbruck.at) is a research institute at the University of Innsbruck engaged in research and development to bring information and communication technologies of the future into today`s world. STI Innsbruck is currently looking for candidates for the following University position with the start date of 15.09.2015 (duration: 4 years)

PhD Student

Responsibilities:

Independent research: writing a doctoral dissertation

Individual teaching and supervision of students

Implementation of research projects

Writing of research papers (workshops, conferences, journals)

Training and further education

Administrative tasks

Required qualifications:

Master's degree in Computer Science

Research interest in areas such as Smart Data, Linked Data, Semantic Web, Semantic Services, Rule-based Systems, Online Communications, Social Media, eTourism

Experience in programming: Java and/or other relevant technologies

Willingness to work on an international team

Willingness to combine formal research with real-world practice in national and international projects

Application:

We are looking forward to receiving your application by 13.06.2015 to hr@sti2.at

Job posting: NLP Staff Applied Scientist at LinkedIn, Dublin, Ireland

At LinkedIn, we regularly process the semi-structured content in the 340+ million member profiles and the content they create on LinkedIn, such as comments, job descriptions, group discussions, and Influencer posts. We are building an NLP (Natural Language Processing) team at LinkedIn and this is a great opportunity to get in on the ground floor.

Responsibilities:

- Design and develop NLP systems and tools.
- Research and evaluate different solutions to NLP problems.
- Produce deliverable results and see them through from development to production.
- Interact and work with remote teams located in different timezones.

Requirements:

- PhD in Computer Science or related discipline. 
- Expertise in several of the following domains: sentiment analysis, information extraction (POS, N/E tagging with HMMs/CRF etc), feature extraction, classification, tokenization, and processing of non-English text.
- Machine Learning & Text mining exposure and familiarity with R, Weka, NTLK etc.
- Solid experience in Java, C++, or another object-oriented language. 
- Excellent communication skills, drive and discipline to get things done. 

We'd prefer if you also have:

- Worked with web-scale traffic and data.
- Experience with Hadoop, Pig, or other MapReduce paradigms.
- Experience with Lucene, SOLR or other open-source IR toolkits.
- Published work in academic conferences or industry circles.
- Involved in consumer-facing product development and design.

To apply go to https://www.linkedin.com/jobs2/view/44208053 or to reach out for more information, please email Deirdre Hogan (dhogan@linkedIn.com) and Jorge Handl (jhandl@linkedin.com).

PhD Student-Assistants Position at The Faculty of Computer and Information Science of the University of Ljubljana

Apply for PhD Student-Assistants Position in 2015/16

The Faculty of Computer and Information Science of the University of Ljubljana offers five PhD Student-Assistant positions for four years (3 years of study and an additional year) starting in academic year 2015/2016. The position offers:

- covered tuition fees for PhD study 

- a monthly salary depending on the candidate's performance.

The call is open for students who are applying for the Computer and Information Science doctoral programme at the Faculty of Computer and Information Science in the 2015/2016 academic year, and who fulfil all enrolment requirements as stated in the call for applications (http://www.fri.uni-lj.si/en/scholarships/teachingassistantphdstudent/)

Responsibilities:

In addition to regular coursework required for doctoral study programme, the obligations of PhD Students-Assistants also include 30 hours per week of participation in the supervisor's research lab as well as drafting and correcting coursework and exams, and consulting the students for 10 hours per week.

Research Topics:

The research work carried out in our 19 research laboratories is very diverse. The research is particularly intense in the field of artificial intelligence and related disciplines, such as machine learning, data mining and computer vision, and applied to different domains from bioinformatics and cognitive modelling to intelligent robotics. Another important research area is data acquisition and management as well as integration of information systems. We are addressing various other research questions from different fields of computer science, information science and software engineering. 

More information on research activities can be found in the survey of activities: http://www.fri.uni-lj.si/file/178716/survey_konna-verzija_v2.pdf

About the Faculty:

The Faculty of Computer and Information Science is the leading teaching and research institution in the field of Computer Science in Slovenia, and in spite of its comparatively short history it has a number of active research groups, as well as a lengthy roster of alumni, some of whom have achieved distinction in various fields of computer science in Slovenia and abroad. 

In 2014, the Faculty relocated to a new premises in Brdo pri Ljubljani. This was the result of a several year-long project to build new facilities for the Faculty of Computer and Information Science and the Faculty of Chemistry and Chemical Technology. It is also the largest project in Slovenia to be co-funded by the European Union and the largest investment in the history of the University of Ljubljana. (https://www.youtube.com/watch?v=FkGeeX7DV6c)

Application Deadline:

The positions are available starting 1 October 2015 and is available for 4 years. For candidates which are not Slovenian nationals, the official deadline for application is 15 May 2015, due to procedures related to recognition of education and residency permits. If foreign candidates are late with applications, they can also apply until 28 August 2015, but we would like to stress the importance of completing all formalities in time.

Contact Details:

For any additional information about the call for applications or doctoral studies at the Faculty of Computer and Information Science, please direct your enquires to Student Affairs (studinfo@fri.uni-lj.si).

Kind regards,
Slavko Žitnik

as. dr. Slavko Žitnik http://zitnik.si/research University of Ljubljana Faculty of Computer & Information Science Laboratory for Data Technologies Večna pot 113, SI-1000 Ljubljana +386 31 543 547 skype: slavkozitnik @szitnik https://linkedin.com/in/szitnik

Data Scientist job in London

Data Scientist Vacancy

Introduction

Signal is looking for a specialist in Information Retrieval, Natural Language Processing or Machine Learning who can help develop the technology needed to drive our new information service. Signal is creating a product that allows our clients to receive a feed of information based on very specific and complex requirements (e.g. "All the news related to IPOs of European technology companies"). We are building this technology using cutting-edge algorithms for different information processing tasks in collaboration with leading universities. The next steps in the business will focus on how allows users to discover new information by navigating through all our information and automatically generating actionable insight from it.

The successful candidate will join our research team whose main goal is to analyse, implement and experiment with different algorithms to solve or improve solutions to different challenges such as summarization, clustering and event detection.

How we work

We currently have a team of 15 people from diverse functional backgrounds (mainly developers and researchers) that work closely together to bring this project forward. We combine technology from several research fields, including machine learning; natural language processing; and information retrieval. We also work in close collaboration with several universities and we encourage the publication of research results from the team in academic conferences. As an example, we have just presented an industry talk and a demonstration (which won the best demonstration award) in ECIR 2015. We are based in Second Home, a vibrant and innovative working space in the heart of London.

Candidate background

A successful candidate will need to be able to propose, implement and evaluate solutions to real-world requirements, while being able to work in a team of developers and researchers. We are looking for a candidate who is ambitious, entrepreneurial and ready to buy into the long-term vision of this company. The ideal candidate should be highly technical, have strong analytical skills, share our innovative values and be self-motivated. Excellent communication skills, being open-minded and inquisitive and having the desire to learn new skills are essential to thrive in our fast-paced multi-disciplinary environment.

Essential skills and qualifications:

MSc or PhD in a field related to Text Analytics (e.g. natural language processing, information retrieval, machine learning or similar), or equivalent commercial experience;

Detailed knowledge of one or more of the following fields:

* Entity Recognition and Disambiguation

* Concept / Topic Extraction

* Document summarization

* Trend Detection

* Sentiment Analysis

Substantial programming experience (preferably in a commercial environment)

Clojure or similar languages (e.g. Java or Python)

Software collaboration and revision control (e.g. Git or SVN)

Desired skills and experiences:

ElasticSearch / Kibana

Cloud computing (e.g. AWS)

Hadoop / Spark etc.

Graph Databases

We Offer

Salary: £30,000 – £50,000 per annum depending on experience

Work Laptop

Stock Options

Conference and training expenses

A continuous learning environment

Contact Details

To apply for this role, please email your CV and a cover letter to jobs@signal.uk.com.

No agencies please.

Regards,

---
Miguel Martinez-Alvarez (PhD., MBCS)

Co-Founder/Head of Research
@SignalHQ
www.signal.uk.com

www.miguelmalvarez.com

Postdoctoral Fellow and Software Engineering Positions available at UMass Medical School

We are recruiting for multiple positions at levels from Post Doctoral Fellow to Software Engineer to participate research and software development in biomedical natural language processing (NLP) and biomedical informatics.  The group's research (http://www.bio-nlp.org/4_research_projects.phtml) involves developing algorithms and tools for gathering, analyzing and interpreting heterogeneous data from multiple sources both clinically and research related. Recruits will lead development efforts in web service tools and search engines that: retrieve and summarize big data in biomedical domain, automatically extracting information from pdf files and extracting text from images, integrate novel biomedical text mining algorithms into the web tools and search engines to enable intelligent semantic search, and mining electronic health record data for pharmacovigilance.

If you are highly motivated and passionate about research in big data processing or software engineering or have in-depth knowledge and hands on implementation experience with web service tools and are interested in learning more about us, please contact elaine.freund@umassmed.edu with your resume or CV and a cover letter.

General Summary of Postdoc Fellow Position: PhD in Computer Science, computational linguistics or Biomedical Informatics with expertise in natural language processing, machine learning or information retrieval with excellent writing and communication skills and ability to work with the research team.  

General Summary of Software Engineer Position:

Under the direction of the Faculty or designee, the Software Engineer I assists with the design, development, implementation and integration of web service tools, search engines, utilities, applications and enhancements in a complex medical/academic research computing environment.

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Open PhD position on Information Retrieval and Machine Learning at Univ. J. Fourier, Grenoble, France

Open PhD position in Machine Learning and Information Retrieval in the University of Joseph Fourier, Grenoble, France.

Duration: 3 years - Starting date: 1st September, 2015
Supervisors: Eric Gaussier (UJF/LIG, France), Parantapa Goswami (UJF/LIG, France)
Project: Smart Support Centers (SSC)
Estimated salary: 1,450 euros/month net (1,750 euros/month gross)
Deadline for applications: 31st May 2015

Title: Latent probabilistic models for large-scale contextual information retrieval
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Description
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More and more information retrieval (IR) environments involve contextual data, in the form of social information such as user profiles, or link data on users' connections, or in the form of information pertaining to the tasks users are involved in. In the context of support centers, retrieving solutions in response to the problems expressed by user queries can be formulated as a contextual IR problem in which user queries are enriched with data collected from different hardware components that are monitored over time.

In many cases, the contextual information one can rely on is however noisy, and there is no obvious way to filter out non-relevant contextual information from relevant one. In social media, for example, user profile information is not important when general queries are considered, whereas it is important for queries specific to an user. Similarly, for support centers, the majority of the collected system monitoring data is not pertinent to retrieve documents and solutions relevant to a given user query. In all these cases, users' information needs are made up of two parts: a "standard" query and (noisy) contextual information.

The goal of this PhD is to develop models and methods that can (a) identify contextual elements pertinent to users' information needs so as to (b) efficiently retrieve the relevant information, and (c) predict future users' needs from users' context, all these operations being done at very large-scale. Among the different approaches one can think of to address these problems, the ones based on latent probabilistic models are particularly interesting as they allow one to capture implicit dependencies between different element types (as textual and numerical contextual elements). In addition, as contextual information is usually temporal, one needs to develop temporal versions of these models. Lastly, it is crucial to develop solutions that can deal with huge amounts of data. The models and methods developed will be evaluated in two contexts: the first one corresponds to social information retrieval based on users profiles and network data; the second one corresponds to search in support centers in which standard queries are associated with information monitored from users' computing environments.

The successful PhD student will work on all the above aspects. He/she will work on the deployment of such models in Big Data architectures, mainly based on Apache Spark environments, in collaboration with the ERODS team of LIG (erods.liglab.fr).

More details can be found in the following link:
http://ama.liglab.fr/jobs/phd-position-ssc-project/

To apply
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The application should include a brief description of research interests and past experience, a CV, degrees and grades, a copy of the Master thesis (or a draft thereof), a motivation letter (short but relevant to this call), and relevant publications if any. Candidates are encouraged to provide letter(s) of recommendation and contact information to reference persons. Please send your application in one single pdf to both eric.gaussier@imag.fr and parantapa.goswami@imag.fr, before 31st May 2015.

Working Environment
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The PhD candidate will be part of the AMA team (http://ama.liglab.fr/) of LIG in Grenoble, France. LIG (http://www.liglab.fr) is a leading institution in Computer Science in France. The AMA team is conducting research in machine learning and information modeling for complex data. Within this framework, the team is interested in developing new theoretical tools, as well as new prototypes that are deployed in information access applications. The team comprises 25 members (including PhD students) who work on several aspects of machine learning and information access, from theory to applications, including statistical learning, data-mining, and cognitive science.

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Eric Gaussier, Prof. Université J. Fourier | LIG (Laboratoire d'Informatique de Grenoble)
e.mail : Eric.Gaussier@imag.fr | website: http://ama.liglab.fr/~gaussier
tel: (+33) (0)4 56 52 03 09 | mob: (+33) (0)6 82 19 79 88
Surface Mail Address: Centre Equation 4 - UFR IM2AG - LIG/AMA BP 53 - F-38041 Grenoble Cedex 9

3-year PhD Scholarship at RMIT University (Melbourne, Australia): Spoken Conversational Search

RMIT University (Melbourne, Australia)'s School of Computer Science and IT (http://www.rmit.edu.au/compsci) has a 3-year scholarship available for a student commencing a PhD on the topic:

- Spoken Conversational Search: Contextual interactive techniques to support effective information search over a speech-only communication channel

This PhD project will focus on developing techniques for summarising search results (e.g., using clustering, topic modeling, result diversity, etc) for effective presentation over speech, and/or developing patterns for conversational interaction with search results and underlying information. The topic is part of a project involving an industry partner that develops conversational interfaces for accessing information for the visually impaired.

Interested students must have a degree in Computer Science or related field. Some background in Interactive Information Retrieval, Natural Language Processing, and/or Spoken Dialogue Systems/techniques is beneficial but not strictly required.

Students applying to Australian PhD programs require a minimum of 4 years of previous tertiary study, with a minor research project component that includes a thesis/report of approximately 10,000 words.

The scholarship is for 3 years and provides a stipend of approximately AU$25,000.

International students are welcome to apply although international tuition fees may apply. However, there is a possibility that such fees would be waived.

Contact lawrence.cavedon@rmit.edu.au for more information and application details.