Speech and Language Processing

Three Postdoctoral Researchers/Project Researchers (Speech processing and deep learning)

The University of Eastern Finland, UEF, is one of the largest multidisciplinary universities in Finland. We offer education in nearly one hundred major subjects, and are home to approximately 15,000 students and 2,500 members of staff. From 1 August 2018 onwards, we’ll be operating on two campuses, in Joensuu and Kuopio. In international rankings, we are ranked among the leading universities in the world.

The Faculty of Science and Forestry operates on the Kuopio and Joensuu campuses of the University of Eastern Finland. The mission of the faculty is to carry out internationally recognised scientific research and to offer research-education in the fields of natural sciences and forest sciences. The faculty invests in all of the strategic research areas of the university. The faculty’s environments for research and learning are international, modern and multidisciplinary.  The faculty has approximately 3,800 Bachelor’s and Master’s degree students and some 490 postgraduate students. The number of staff amounts to 560. http://www.uef.fi/en/lumet/etusivu

We are now inviting applications for three Postdoctoral Researcher/Project Researcher positions in speech processing and deep learning funded by Academy of Finland, School of Computing, Joensuu Campus.

• Two positions in automatic speaker verification, voice conversion, anti-spoofing (NOTCH project)
• One position in deep reinforcement learning for physical agents (DEEPEN project)

The two projects share similarities in terms of machine learning methods being used and developed further, but are otherwise differently focused.

The NOTCH research project (NOn-cooperaTive speaker CHaracterization), being led by Associate Professor Tomi Kinnunen, aims at advancing state-of-the-art in automatic speaker verification (defense) and voice conversion (attack) under a generic umbrella of non-cooperative speech, whether being induced by spoofing attacks, disguise, or other intentional voice modifications. A successful applicant needs to have background in speaker verification, anti-spoofing, voice conversion, machine learning or closely related topics.

The DEEPEN research project (Deep Reinforcement Learning for Physical Agents) is run in co-operation between UEF and robotics group at Aalto University. UEF’s part, lead by Senior Researcher Ville Hautamäki, aims at designing new statistical models for simulated robot control and to take steps towards solving the so-called “reality gap” problem.  The post-doc may also contribute to speech and deep learning topics. A successful applicant needs to have background in deep learning, reinforcement learning, speech technology or machine vision. Practical experience in DRL research environments (e.g. VizDoom or MuJoCo), will be counted as a plus.

The Machine Learning group of the School of Computing, at the facilities of Joensuu Science Park, provides access to modern research infrastructure and is a strongly international working environment. We hosted the Odyssey 2014 conference, were a partner in the H2020-funded OCTAVE project, and are a co-founder of the Automatic Speaker Verification and Countermeasures (ASVspoof) challenge series (http://www.asvspoof.org/).

A person to be appointed as a postdoctoral researcher shall hold a suitable doctoral degree that has been awarded less than five years ago. If the doctoral degree has been awarded more than five years ago, the post will be one of a project researcher. The doctoral degree should be in  spoken language technology, electrical engineering, computer science, machine learning or a closely related field.  Researchers finishing their PhD in the near future are also encouraged to apply for the positions.  However, they are expected to hold a PhD degree by the starting date of the position. We expect strong hands-on experience and creative out-of-the-box problem solving attitude. A successful applicant needs to have an internationally proven track record in topics relevant to the project he or she applies to.

English may be used as the language of instruction and supervision in these positions.

The positions will be filled from earliest January 1, 2018 for a period of 12 months. The continuation of the position will be agreed separately. The position will be filled for a fixed term due to pertaining to a specific project (Postdoctoral researcher positions shall always be filled for a fixed term, UEF University Regulations 31 §).

The salary of the position is determined in accordance with the salary system of Finnish universities and is based on level 5 of the job requirement level chart for teaching and research staff (€2.865,30/ month). In addition to the job requirement component, the salary includes a personal performance component, which may be a maximum of 46.3% of the job requirement component.

For further information on the position, please contact (NOTCH): Associate Professor Tomi Kinnunen, email: tkinnu@cs.uef.fi, tel. +358 50 442 2647 and (DEEPEN): Senior Researcher Ville Hautamäki, email: villeh@cs.uef.fi, tel. +358 50 511 8271.  For further information on the application procedure, please contact: Executive Head of Administration Arja Hirvonen, tel. +358 44 716 3422, email: arja.hirvonen@uef.fi.

A probationary period is applied to all new members of the staff.

You can use the same electronic form to apply for both research projects. The electronic application should contain the following appendices:

• a résumé or CV
• a list of publications
• copies of the applicant's academic degree certificates/ diplomas, and copies of certificates / diplomas relating to the applicant’s language proficiency, if not indicated in the academic degree certificates/diplomas
• motivation letter
• a cover letter indicating the position to be applied for
• The names and contact information of at least two referees are requested in the application form.

The application needs to be submitted no later than December 22, 2017 (by 24:00 EET) by using the electronic application form.

Navigate to http://www.uef.fi/en/uef/en-open-positions and search for “Three Postdoctoral Researchers/Project Researchers (Speech processing and deep learning)” to find the link to the electronic application form. 

Manual operation of hearing assistive devices is cumbersome in various situations. With advances in machine learning and speech technology, voice interfaces due to their convenience will be widely deployed for hearing assistive devices and they can be personalized and offer richer functionalities. Hearing assistive devices are characterized by strict memory and computational complexity constraints and the fact that they are expected to operate flawlessly, even in acoustically challenging situations. This PhD project aims to develop personalized, noise-robust and low-resource voice control systems for hearing assistive devices, using microphone signals and other modalities.

For more details, please refer to http://www.stillinger.aau.dk/vis-stilling/?vacancy=936714.

Lead Speech Recognition Engineer

Location: Cambridge, UK

Contact: careers@speechmatics.com

Background

Speechmatics is a leader in automatic speech recognition (ASR). Using proprietary technology, we have built one of the most accurate ASR systems in the world, with a vision to power a voice-enabled economy. We are already working at a time when the global economy is actively adopting all types of speech-related technologies. In developing our technology we combine our years of experience, the latest developments in the field and our own focus on cutting-edge research to produce a world-class service.

In the office, we pride ourselves on a relaxed but productive environment whilst we stay in touch with the progress of others by attending both academic and commercial conferences and have fun together with regular outings (in the past we have been punting, go-karting, attended a cooking workshop and played bubble football...).

We are expanding rapidly and are seeking more people in the coming months to help us keep pushing the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented speech scientist to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is working on our core ASR capabilities to improve our speed and accuracy and develop novel features so that we can support all languages. Your work will feed into ‘Auto-Auto’, our ground-breaking framework to support the building of ASR models, and hence the delivery of every language pack published by the company. You will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a small team, you will need to be a team player who thrives in a fast paced environment, with a focus on rapidly moving research developments into products. Bringing skills to the team is as important as a can-do attitude. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Ensuring that our speech recognition meets or exceeds that published by others
• Improving our core modelling (acoustic, pronunciation, language)
• Leading the extension of our ML framework so that we can build any language

Experience

Essential

• MSc, PhD or equivalent experience in the academic aspects of speech recognition
• Several years practical experience in speech recognition, covering all aspects (acoustic, pronunciation and language modelling as well as decoders/search)
• Experience working with standard speech and ML toolkits, e.g. Kaldi, KenLM, TensorFlow, etc.
• Solid programming skills with Python and / or C/C++
• Experience using Unix/Linux for big data

Desirable

• PhD degree
• Experience of team leadership and line management
• Experience of working in an Agile framework
• Expertise in modern speech recognition, including WFSTs, lattice processing, neural net (RNN / DNN / LSTM), acoustic and language models, Viterbi decoding
• Comprehensive knowledge of machine learning and statistical modelling
• Experience in deep machine learning and related toolkits, e.g. Theano, Torch, etc.
• Deep expertise in Python and/or C++ software development
• Experience working effectively with software engineering teams or as a Software Engineer

Salary We offer a competitive salary, bonus scheme, pension contribution matching (up to 5%) and a generous EMI share option scheme. We also have several additional benefits including holiday purchase, massages, fully stocked beer fridge, Cyclescheme, fruit boxes and many more. The overall package will depend on your motivations and level of experience. 

EMR.AI Inc., San Francisco, CA

RESEARCH SCIENTIST, SPEECH RECOGNITION

Headquartered in San Francisco, CA, EMR.AI Inc. is a leading provider of AI solutions to the medical sector.  EMR.AI transforms unstructured information, in form of written, spoken, or typed reports, clinical test results, and radiographs into international standard codes saved in common EMR systems. The wealth of discrete medical data provided through this transformation in conjunction with EMR.AI's suite of medical analytics solutions enables stakeholders, practitioners, researchers, health providers, and policy makers to obtain a comprehensive picture of the available medical data in their organization.

SUMMARY

EMR.AI Research & Development has openings for Research Scientists in the field of Speech Recognition in our Downtown San Francisco offices.  Scientists will work on projects spanning a variety of tasks including the semantic interpretation of spoken medical reports, the design of language models for a variety of speech recognition and NLP tasks, the summarization of spoken language in the medical domain, the incorporation of lexica, ontologies, relational databases, and other sources of structured and unstructured knowledge sources into EMR.AI’s medical ASR and NLP tool set, and others.

This is a unique opportunity to be part of a cutting-edge R&D team in the epicenter of the world’s AI tech industry with true impact on medical research.

RESPONSIBILITIES
 

• Train, tune, and test acoustic, lexical, and language models for speech recognition, speaker identification, and speaker diarization, for batch and live recognition.
• Innovate components of the speech recognition pipeline to create excellent results on a challenging task, including feature extraction, noise reduction, speaker adaptation, dimensionality reduction, acoustic, lexical, and language modeling, decoding, and syntactic and semantic post-processing.
• Process huge corpora of medical spoken reports and dialog interactions to perform syntactic and semantic analyses using both existing tool benches, proprietary and open-source, as well as self-developed algorithms and techniques.
• Produce high-quality programs and scripts to embed scientific algorithms into effective prototypes and demos to be shared with EMR.AI’s leadership team, its customers, partners, and vendors.
• Create and document technological innovations by means of patent disclosures, scientific publications, media alerts, and other channels.
• Work closely with EMR.AI’s NLP team and its software engineering division to produce innovative and effective solutions for a range of AI products and services in the medical domain.
• Represent the R&D division in communications with EMR.AI’s leadership team, its customers, partners, and vendors at meetings, conventions, and other venues as well as in written statements.

SKILLS

PhD in computer science, computational linguistics, electrical engineering, or a related field.  Experience in the state of the art of speech recognition and its standard tools is required.  Candidates must be very skilled in programming and must have a proven scientific track record.  They must be excellent team players, including with distributed teams, and strong in oral and written English communication.  Knowledge of the US medical sector is desirable, so are experience with start-ups and strong scientific connections throughout the Bay Area and beyond.

BENEFITS

EMR.AI offers competitive salaries, an excellent benefit package, and a stimulating work environment in the heart of San Francisco with manifold local, domestic, and international commercial and academic partnerships.

HOW TO APPLY

Please send your application documents to jobs@emr.ai

CONTACT

EMR.AI Inc.

90 New Montgomery St #400
San Francisco, CA 94105, USA

phone: +1-415-590-7721
e-mail: info@emr.ai
www: http://emr.ai

Experience IT – Intuitive Technology: this principle guides our work at the European Media Laboratory. We are an IT enterprise, based in Heidelberg, Germany, focusing on the automatic conversion of speech into text for a variety of markets. Speech technologists and IT specialists research, develop and use state-of-the-art large-vocabulary automatic speech recognition technologies, including deep learning, to convert spoken audio into structured textual data and actions. Our products currently comprise server-based speech recognition for speech analytics, media transcription, voice messaging, voice search and dictation as well as on-device language model and grammar-based speech recognition solutions for house control, car control and smartphones. For further details on our activities please have a look at our “Best-Practice”-Examples (http://www.eml.org/downloads/EML_Best_Practice_eng_web.pdf).

For our research and development projects we hire at the earliest possible date experienced

Technologists (m/f) for Speech Processing Systems

meeting the following criteria:

• Hands-on experience in developing state-of-the-art technologies for speech recognition and / or language understanding systems.
• Experience in evaluating and tuning speech recognition and understanding systems.
• Fluency in programming languages such as C++, Java, and Python for Linux, Windows, Android or iOS.
• Degree in computer science, mathematics, computational linguistics or related disciplines.

Successful candidates should have several years of applied and theoretical experience in several of the areas mentioned; a PhD or an equivalent level of applied expertise would be helpful. All positions require an application-oriented perspective and a willingness to listen to and act upon customers’ concerns.

Interested? Please send us your written application with the subject "Job advertisement EML/07/2017" as soon as possible but no later than October 16, 2017 to the following address:

Prof. Dr. Andreas Reuter, Managing Director, EML European Media Laboratory GmbH, Berliner Straße 45, 69120 Heidelberg or by E-Mail to Dr. Siegfried (Jimmy) Kunzmann (bewerbung@eml.org), Manager R&D.

Senior Speech Recognition Engineer

Location:         Cambridge, UK

Background

Speechmatics is a leader in automatic speech recognition (ASR). Using proprietary technology, we have built one of the most accurate ASR systems in the world, with a vision to power a voice-enabled economy. We are already working at a time when the global economy is actively adopting all types of speech-related technologies. In developing our technology we combine our years of experience, the latest developments in the field and our own focus on cutting-edge research to produce a world-class service.

In the office, we pride ourselves on a relaxed but productive environment whilst we stay in touch with the progress of others by attending both academic and commercial conferences and have fun together with regular outings (in the past we have been punting, go-karting, attended a cooking workshop and played bubble football...).

We are expanding rapidly and are seeking more people in the coming months to help us keep pushing the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented scientist to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is responsible for Auto-Auto, our ground-breaking framework to support the building of ASR models, and hence the delivery of every language pack published by the company. This will involve maintaining and improving our pipeline, keeping our speech recognition at the head of the field and solving the challenges of a growing language portfolio.

Because you will be joining a small team, you will need to be a team player who thrives in a fast paced environment, with a focus on product delivery. Bringing skills to the team is as important as a can-do attitude. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Our work typically relies on very large quantities of data, state-of-the-art methods (and our secret ingredients). Auto-Auto and the languages we are covering is core to our business. You should therefore be passionate about building products that will be used in businesses and homes worldwide.

Key Responsibilities

• Delivering high quality language models on time.
• Cracking the challenges of an ever-growing portfolio (e.g. think tones, synthetics languages with rich morphology or agglutination, under resourced languages, etc.) with pragmatism and flexibility in mind.
• Participating in the software development cycle of Auto-Auto.
• Keeping an eye on the field and technological advances to stay ahead of the game.
• Helping with the never ending problem of data acquisition: we always need more.

Experience

• Graduate degree in statistics, engineering, mathematics, or computer science.
• Expertise in key natural language processing technologies, such as speech recognition, text to speech or natural language understanding.
• Experience working with standard NLP toolkits, e.g. Kaldi, KenLM, etc.
• Solid programming skills with at least one scripting language (e.g. Python, Perl, Ruby, etc).
• Experience using Unix/Linux.
• Analytical mind-set with a data-driven approach to making decisions and real attention to detail.
• Experience of working within a team.
• PhD degree.
• Demonstrable commercial work experience in a directly related field.
• Expertise in modern speech recognition, including WFSTs, lattice processing, neural net (RNN / DNN / LSTM), acoustic and language models, Viterbi decoding.
• Comprehensive knowledge of machine learning and statistical modelling.
• Experience in deep machine learning and related toolkits, e.g. Theano, Torch, etc.
• Expertise in Python and/or C++.
• Experience working effectively with software engineering teams or as a Software Engineer.

Salary

We offer a competitive salary, bonus scheme, pension contribution matching (up to 5%) and a generous EMI share option scheme. We also have several additional benefits including holiday purchase, massages, fully stocked beer fridge, Cyclescheme, fruit boxes and many more.

The overall package will depend on your motivations and level of experience. 

Lead Speech Recognition Engineer

Location:         Cambridge, UK

Background

Speechmatics is a leader in automatic speech recognition (ASR). Using proprietary technology, we have built one of the most accurate ASR systems in the world, with a vision to power a voice-enabled economy. We are already working at a time when the global economy is actively adopting all types of speech-related technologies. In developing our technology we combine our years of experience, the latest developments in the field and our own focus on cutting-edge research to produce a world-class service.

In the office, we pride ourselves on a relaxed but productive environment whilst we stay in touch with the progress of others by attending both academic and commercial conferences and have fun together with regular outings (in the past we have been punting, go-karting, attended a cooking workshop and played bubble football...).

We are expanding rapidly and are seeking more people in the coming months to help us keep pushing the boundaries of speech recognition. This is an opportunity to join a high growth team and form a major part of its future direction.

The Opportunity

We are looking for a talented speech scientist to help us build the best speech technology for anybody, anywhere, in any language. You will be a part of a team that is working on our core ASR capabilities to improve our speed and accuracy and develop novel features so that we can support all languages.   Your work will feed into ‘Auto-Auto’, our ground-breaking framework to support the building of ASR models, and hence the delivery of every language pack published by the company.   You will be responsible for keeping our system the most accurate and useful commercial speech recognition available.

Because you will be joining a small team, you will need to be a team player who thrives in a fast paced environment, with a focus on rapidly moving research developments into products. Bringing skills to the team is as important as a can-do attitude. We strongly encourage versatility and knowledge transfer within the team, so we can share efficiently what needs to be done to meet our commitments to the rest of the company.

Key Responsibilities

• Ensuring that our speech recognition meets or exceeds that published by others
• Improving our core modelling (acoustic, pronunciation, language)
• Leading the extension of our ML framework so that we can build any language

Experience

• MSc, PhD or equivalent experience in the academic aspects of speech recognition
• Several years practical experience in speech recognition, covering all aspects (acoustic, pronunciation and language modelling as well as decoders/search)
• Experience working with standard speech and ML toolkits, e.g. Kaldi, KenLM, TensorFlow, etc.
• Solid programming skills with Python and / or C/C++
• Experience using Unix/Linux for big data

• PhD degree
• Experience of team leadership and line management
• Experience of working in an Agile framework
• Expertise in modern speech recognition, including WFSTs, lattice processing, neural net (RNN / DNN / LSTM), acoustic and language models, Viterbi decoding
• Comprehensive knowledge of machine learning and statistical modelling
• Experience in deep machine learning and related toolkits, e.g. Theano, Torch, etc.
• Deep expertise in Python and/or C++ software development
• Experience working effectively with software engineering teams or as a Software Engineer

Salary

We offer a competitive salary, bonus scheme, pension contribution matching (up to 5%) and a generous EMI share option scheme. We also have several additional benefits including holiday purchase, massages, fully stocked beer fridge, Cyclescheme, fruit boxes and many more.

The overall package will depend on your motivations and level of experience. 

Department of Computer Science, University of Crete, Greece

Post-doctoral Research Associate in Advanced Deep Neural network Architectures for ASR

(Fixed Term)

SALARY: €24000-€28000 per year

CLOSING DATE: 30 June 2017

REFERENCE: ASR1

TO APPLY: Send detailed CV, a motivation letter and 3 major publications to yannis@csd.uoc.gr

In the past few years, Deep Neural Networks (DNNs) have achieved tremendous success for many supervised machine learning tasks, including acoustic modelling for Automatic Speech Recognition (ASR). Advanced models such as Convolutional Neural Networks (CNNs) and Long Short Term Recurrent Neural Networks (LSTMs) have contributed to recent empirical breakthroughs. Network depth has played perhaps the most important role in these successes. However, increased depth represents challenges in the optimization of the network and despite the efforts to overcome these challenges some of the optimization issues are still important resistant. Advanced networks such as highway networks and (wide) residual networks seems to offer solutions to these issues.

This position represents an ideal opportunity to work in or move into advanced deep neural networks, as it will involve collaborating widely across academia and industry, and working on one of the most pressing research areas of machine learning for the development of robust ASR systems.

Based in Heraklion Crete the post will be with Prof. Yannis Stylianou and Dr. Vassilis Tsiaras as part of the speech processing group within the Department of Computer Science at the University of Crete. You will explore a rich set of network architectures and thoroughly examine how several different aspects affect the accuracy of ASR. The work will be performed within the framework of advanced deep neural network architectures for various signal processing tasks including 1D and 2D signals. The focus of the post will be to perform various experiments with well-known architectures, explore and suggest modifications, process and reshape knowledge from various signal processing/classification tasks towards speech processing for the purpose of ASR. Outcomes will directly feed into improvements of ASR systems in-house working with state-of-the art ASR tasks (i.e., CHiME4, REVERB, etc) and of our industrial partners using real-life data.

The post involves travel to international conferences and project meetings with our academic and industrial partners. There will be the possibility to co-advise doctoral students and potentially other teaching opportunities.

Applicants should have a doctorate in speech signal processing area for ASR, computer science, applied mathematics or related field and ideally a strong background in deep learning and mathematics. Knowledge of deep learning systems such as Tensorflow or Theano etc and ASR systems like Kaldi are an advantage. Proficiency in computer programming in C and/or Python are expected.

Informal inquiries should be directed to Prof. Yannis Stylianou by email, yannis@csd.uoc.gr

Fixed term: In the first instance, the funding supporting the post is for two years. We are expecting project extension which will provide funding for a further 7-12 months for this post.

Interviews are expected to take place the week commencing 10^th July 2017.

Expected start date: September 2017, however earlier and later start dates will be considered.

To apply, please send detailed CV, a motivation letter and 3 major publications of yours to: yannis@csd.uoc.gr (Prof. Yannis Stylianou)

Department of Computer Science, University of Crete, Greece

Post-doctoral Research Associate in Data Augmentation in the context of Deep Neural network ASR

(Fixed Term)

SALARY: €24000-€28000 per year

CLOSING DATE: 30 June 2017

REFERENCE: ASR2

TO APPLY: Send detailed CV, a motivation letter and 3 major publications to yannis@csd.uoc.gr

In the past few years, Deep Neural Networks (DNNs) have achieved tremendous success for many supervised machine learning tasks, including acoustic modelling for Automatic Speech Recognition (ASR). Advanced models such as Convolutional Neural Networks (CNNs) and Long Short Term Recurrent Neural Networks (LSTMs) have contributed to recent empirical breakthroughs. However, deep learning methods are quite demanding in the amount of data for training an acoustic model for ASR and as a result significant amounts of transcribed data has become available for training use. But data transcription is a quite expensive and time consuming process. On the other hand, just adding data recorded in real-world conditions puts serious constraints on the efficient training of the acoustic models. Various works on data augmentation show that word error rate (WER) can be significantly reduced if proper augmented data are processed.

This position represents an ideal opportunity to work in or move into data augmentation research area in the context of advanced deep neural networks for ASR, as it will involve collaborating widely across academia and industry, and working on one of the most pressing research areas of machine learning for the development of robust ASR systems.

Based in Heraklion Crete the post will be with Prof. Yannis Stylianou and Dr. George Kafentzis as part of the speech processing group within the Department of Computer Science at the University of Crete. You will design and develop smart approaches for spoken data augmentation for the purpose of multi-condition training of deep learning-based ASR systems. The work will be performed within the framework of advanced deep neural network architectures for various ASR tasks. The focus of the post will be to perform various experiments with spoken data generation, explore and suggest modifications, process and reshape knowledge from various signal processing for the purpose of ASR. Outcomes will directly feed into improvements of ASR systems in-house working with state-of-the art ASR tasks (i.e., AURORA-4, CHiME4, REVERB, etc) and of our industrial partners using real-life data.

The post involves travel to international conferences and project meetings with our academic and industrial partners. There will be the possibility to co-advise doctoral students and potentially other teaching opportunities.

Applicants should have a doctorate in speech signal processing area for ASR, statistical speech synthesis and voice conversion, audio signal processing, computer science, applied mathematics or related field and ideally a strong background in deep learning and mathematics. Knowledge of deep learning systems such as Tensorflow or Theano etc and ASR systems like Kaldi are an advantage. Proficiency in computer programming in C and/or Python are expected.

Informal inquiries should be directed to Prof. Yannis Stylianou by email, yannis@csd.uoc.gr

Fixed term: In the first instance, the funding supporting the post is for two years. We are expecting project extension which will provide funding for a further 7-12 months for this post.

Interviews are expected to take place the week commencing 10^th July 2017.

Expected start date: September 2017, however earlier and later start dates will be considered.

To apply, please send detailed CV, a motivation letter and 3 major publications of yours to: yannis@csd.uoc.gr (Prof. Yannis Stylianou)