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https://pub.refline.ch/845721/3714/++publications++/1/index. html
** Technische Universität Berlin - Department of Computer Science ** Starting as soon as possible a fully funded research position is available at the Distributed Artificial Intelligence Laboratory at the TU-Berlin. The DAI-Labor at the Technische Universität Berlin is looking for a doctoral research associate in the areas of semantic service composition, artificial intelligence, smart environments and electric mobility. The candidate will be responsible for including leading a team of students, managing projects, writing project proposals as well as communicating with national and international partners. Assignment: • Research in semantic service composition, adaptive systems, user modelling, and semantic service interconnection • Evaluation in the areas of smart environments, e-mobility services, adaptive and dynamic service compositions • Leading and supervision of a team of students • Preparation of scientific publications • Conceptual design of projects • Acquisition and management of third party funded projects • Communication with external project partners Your profile • Master degree in computer science or a discipline related to the research area • Knowledge in the field of model-based development and model-driven engineering would be appreciated. • Experience in project and team management, very good social and effective communication skills • Willingness for independent scientific work • Maker and doer, used to take initiative, and a team player • Excellent spoken and written English, German is a plus • Experience in teaching We offer • Exciting topics and a vibrant environment • Excellent state-of-the-art infrastructure with access to new and emerging technologies • A smart home environment and living lab for evaluation of results • Close collaboration with national and international partners from research institutes, universities and industry • Possibility to pursue Phd About the DAI-Labor The DAI-Labor and the chair "Agent technologies in business applications and telecommunication" at the Technische Universität Berlin, headed by Prof. Dr. Dr. hc Sahin Albayrak, perform research and development in order to provide solutions for a new generation of systems and services – "smart services and smart systems". Research at the DAI-Labor is done in competence centers, which address different areas, ranging from investigation of the foundations of distributed systems and machine learning, to enhancing security in networks and interactive systems. The scientific grounding and results of the competence centers are used to develop system solutions in different application centers. The application centers focus on the development of intelligent services and systems to deal with current and future challenges of society. State-of-the-art testbeds allow validating and demonstrating these services in realistic scenarios. Close cooperation with industry partners ensures an approach that is both practical and solution oriented. All of this allows the DAI-Labor to develop technologies within a university environment that meets even the highest industry standards. For further information regarding this position and our institute, please see our website http://www.dai-labor.de, or contact Johannes Fähndrich at johannes.faehndrich@dai-labor.de<mailto:johannes.faehndrich@ dai-labor.de>. Applications including a CV, a brief description of their research interests, copies of their university degree and/or study transcripts, and a list of publications should be sent to bewerbungNGS@dai-labor.de< mailto:bewerbungNGS@dai-labor. de>, with reference IV-496/14 no later than February 27th, 2015. To apply please send you application to: Technische Universität Berlin - Der Präsident - , Fakultät IV, Institut für Wirtschaftsinformatik und Quantitative Methoden, DAI-Labor, Prof. Dr. Dr. Albayrak, Sekr. TEL 14, Ernst-Reuter-Platz 7, 10587 Berlin. More details can be found here: http://www.personalabteilung. tu-berlin.de/menue/jobs/ externe_jobs/ ______________________________ _________________
Apologies for cross-postings.
Master internship and PhD position in Conditional Random Field learning for Sentiment Analysis in
Phone Conversations
Telecom ParisTech (http://www.telecom-paristech.
37 rue Dareau, 75014 Paris - France
Advisors:
Chloé Clavel (http://clavel.wp.mines-
Slim Essid (http://perso.telecom-
Starting date: Anytime from February to June 2015
Funding: Secured with the Telecom ParisTech Machine Learning for Big Data Chaire
(http://
Keywords: Sentiment Analysis, Opinion Mining, Machine Learning, Conditional Random Fields, Natural
Language Processing, Audio and Speech Processing
Applications are invited for a 3 to 6 month master internship to be continued by work towards a PhD
for a duration of 36 months. Outstanding candidates will be considered to start the PhD work
immediately, without doing the internship.
Topic:
Sentiment analysis and opinion mining have gained an increasing interest with the explosion of
textual content conveying users’ opinions (e.g. film reviews, forum debates, tweets). Hence, natural
language processing researchers have dedicated a great deal of effort into the development of
methods amenable to opinion detection in such texts, though often simplifying the problem to one of
classification over the valence (positive vs negative) and intensity axes. As for sentiment analysis
in speech signals, there have been hardly any attempts. Further challenges are posed in this case
where not only should the special features of spoken language be taken into account, but also
prosodic features and the potential errors of automatic speech recognition systems.
The research work planned will focus on the development of sentiment analysis methods in the context
of phone conversations. The privileged research direction will consist in exploiting the appraisal
theory adapted to the verbal content (as defined by psycho-linguists) in order to create effective
computational models of evaluative expressions. In particular, Conditional Random Fields will be
considered with feature functions encoding the semantic rules usually used for our task.
IDEAL CANDIDATE:
Master’s student or Master’s degree with background in
- Machine learning / pattern recognition
- Speech processing, natural language processing
- Excellent programming skills (Python, Java, C/C++)
- Good English level
APPLICATIONS :
To be sent to chloe.clavel@telecom-
- Curriculum Vitae
- Statement of interest (in the body of the email)
- Academic records
- List of references
Incomplete applications will not be considered.