Application Form
PhD Studentship in Neural Language Generation [PhD_NLG_AB]

JobRef: 9275
  • Accepted file types: pdf.
  • Accepted file types: pdf.

PhD Studentship in Neural Language Generation [PhD_NLG_AB]

Level:PhD
POSTED:June 23, 2021
LOCATION:Dublin City University
CLOSES:July 14, 2021
Duration:4 Years
Reports to:Prof Anye Belz
Salary:Annual stipend of €18,000 (non taxed)
Closing Date:July 14, 2021

Why ADAPT?

  • Contribute to the ADAPT research agenda that pioneers and combines research in AI driven technologies: Natural Language Processing, Video/Text/Image/Speech processing, digital engagement & HCI, semantic modeling, personalisation, privacy & data governance. 
  • Work with our interdisciplinary team of leading experts from the complementary fields of Social Sciences, Communications, Commerce/Fintech, Ethics, Law, Health, Environment and Sustainability.
  • Leverage our success.  ADAPT’s researchers have signed 43 collaborative research projects, 52 licence agreements and oversee 16 active commercialisation funds and 52 commercialisation awards. ADAPT has won 40 competitive EU research projects and obtained €18.5 million in non-exchequer non-commercial funding. Additionally, six spinout companies have been formed. ADAPT’s researchers have produced over 1,500 journal and conference publications and nearly 100 PhD students have been trained. 

As an ADAPT funded PhD researcher you will have access to a network of 85 global experts and over 250 staff as well as a wide multi-disciplinary ecosystem across 8 leading Irish universities. We can influence and inform your work, share our networks and collaborate with you to increase your impact, and accelerate your career opportunities. Specifically we offer: 

  1. Opportunity to build your profile at international conferences and global events.
  2. A solid career pathway through formalised training & development, expert one-on-one supervision and exposure to top specialists.
  3. A fully funded, 4 year PhD postgraduate studentship which includes a stipend of €18,000 per annum (non taxed), along with equipment, and annual travel funding. 
  4. Funding for annual student fees. 

 

Research Topic 

The successful applicant will be supervised by, and work closely with, Prof Anya Belz, Science Lead in the Digital Content Transformation Strand in ADAPT, and will be embedded in an expanding group of researchers working on language generation methods that are (1) high quality, (2) semantically controllable, (3) resource efficient, (4) explainable, (5) non-biased, and (6) informatively evaluated.

This studentship is in the area of language generation. A range of different topics are possible, but proposals are expected to involve auto-regressive, non-auto-regressive, RL or hybrid approaches to NLG, and to align with one of the above 6 goals.

Applicants are advised to contact Prof Belz (anya.belz@adaptcentre.ie) to discuss possible research topics prior to writing the outline research proposal that is required as part of submitting their application (see below).

On completion of the PhD program the candidate

  • Will have demonstrated understanding of the problems related to language generation methods , and have mastered  the skills and methods of research in this field;
  • Will have demonstrated capabilities of defining, designing and implementing appropriate research methodologies with academic integrity and made substantial contributions that extend the knowledge in the field;
  • Be able to communicate concepts and research outputs with their peers and the research community at large and with people outside the field. 

Training & Development

Advanced training, in the form of accredited modules, known as ‘Graduate Training Elements’ or GTEs, are an important aspect of DCU’s graduate research experience. Information on graduate training at DCU is available here: https://www.dcu.ie/graduatestudies/training.shtml. The successful student will be expected to undertake and pass a minimum of 20 credits of taught modules for the duration of their studies.

As part of the studentship you will also undertake the following training opportunities: 

  • Orientation
  • Health & Safety 
  • Intellectual Property (IP) 
  • Data Protection (GDPR) 
  • Other training may need to be undertaken when required

Minimum qualifications:

  • A BSc or equivalent degree in computer science or related field. Some experience with neural methods for natural language processing.
  • English language requirements for non-native speakers of English is available here: https://www.dcu.ie/registry/english.shtml

Preferred qualifications:

  • A Masters level degree or equivalent in Natural Language Processing or a related subject, 
  • Some prior research experience in Natural Language Generation,
  • Some prior experience of collaborating and publishing on research projects.

Application Process

Each application should only consist of:

  1. Detailed curriculum vitae, including – if applicable – relevant publications,
  2. Transcripts of degrees,
  3. The name and email contacts of two academic referees,
  4. An outline research proposal aligned with the research topic description above and no more than 4 pages in length, and
  5. A cover letter/letter of introduction (max 2 pages). In the letter, applicants should include the following details:
    1. A brief explanation of your interest in the research to be conducted and why you believe you are suitable for the position.
    2. Details of your final year undergraduate project (if applicable).
    3. Details of your MSc project (if applicable).
    4. Details of any relevant modules previously taken, at undergraduate and/or Master level.
    5. Details of any relevant work experience (if applicable).

 

Diversity

ADAPT is committed to achieving better diversity and gender representation at all levels of the organisation, across leadership, academic, operations, research staff and studentship levels. ADAPT is committed to the continued development of employment policies, procedures and practices that promote gender equality. On that basis we encourage and welcome talented people from all backgrounds to join ADAPT.


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