PhD Fellow in Natural Language Processing

University of Copenhagen Department of Computer Science

Denmark

(211-0298/19-2H) PhD Fellow in Natural Language Processing

PhD Fellow in Natural Language Processing
Machine Learning Section
Department of Computer Science
Faculty of Science

University of Copenhagen

The Machine Learning Section at the Department of Computer Science, Faculty of Science at University of Copenhagen is offering a PhD scholarship in Natural Language Processing commencing between 1 March 2020 and 1 April 2020

Description of the scientific environment
The Machine Learning Section provides a strong, international and diverse environment for research within Theoretical and Applied Machine Learning, Natural Language Processing and Understanding, Information Retrieval, and Medical Image Analysis. It is housed within the main Science Campus, which is centrally located in Copenhagen. For details, see https://di.ku.dk/english/research/machine-learning/. The successful candidate will join Isabelle Augenstein’s Natural Language Understanding research group (https://copenlu.github.io).

Project description
Word choice is strongly influenced by the gender of the speaker and the referent. Much of the prior research on gendered language has focused on laboratory studies and smaller corpora; however, more recent work has begun to focus on larger-scale datasets. These studies compare the adjectives or verbs that modify each noun in a particular gendered pair of nouns, such as boy–girl, aggregated across a given corpus. In our recent pilot study, we focus on large-scale detection of gender bias for any adjectives or verbs modifying common nouns (Hoyle et al., 2019). Despite its importance, the study has several strong limitations, which will be addressed in this project, namely: 1) the methods cannot directly be used to detect gender bias towards entities, such as persons; 2) it focuses on English only. Addressing these two limitations is not straight-forward, as it 1) requires methods for understanding which words describe the attitude towards an entity; and 2) requires cross-lingual modelling. This project will result in a general methodology for detecting and quantifying gender bias towards entities in any language, which can be applied in downstream applications. The project use case, detecting gender bias towards politicians on social media, is expected to generate new insights on its own.

The principal supervisor is Assistant Professor Isabelle Augenstein, Department of Computer Science, e-mail augenstein@di.ku.dk. The PhD student will be co-supervised by Assistant Professor Ryan Cotterell, ETH Zurich. Travel funding for bilateral visits is available.

Job description
The position is available for a 3-year period. The key tasks as a PhD student at SCIENCE are:

  • To carry out your research project with increasing autonomy from your supervisors
  • To write scientific articles and your PhD thesis
  • To attend PhD courses on general skills development, e.g. academic writing
  • To disseminate your research nationally and internationally
  • To assist in the teaching of courses, typically by working as a lab assistant for one 8-week course per year

Formal requirements
Applicants should hold a MSc degree or equivalent in Computer Science or a related field, and have good written and oral English skills. The assessment of your qualifications will also be made based on previous scientific publications (if any) and relevant work experience.

Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

The starting salary is currently at a minimum DKK 328.355 (approx. €43,750) including annual supplement (+ pension at a minimum DKK 53,360). Negotiation for salary supplement is possible

Application Procedure
The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include

  • Cover Letter, detailing your motivation and background for applying for the specific PhD project
  • A maximum 2-page research statement, explaining how you would approach the project
  • CV
  • Diploma and transcripts of records (BSc and MSc)
  • Other information for consideration, e.g. list of publications (if any),

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

The deadline for applications is Sunday 1 December 2019, 23:59 GMT +1

After the expiry of the deadline for applications, the authorised recruitment manager selects applicants for assessment on the advice of the Interview Committee. Afterwards, an assessment committee will be appointed to evaluate the selected applications. The applicants will be notified of the composition of the committee and the final selection of a successful candidate will be made by the Head of Department, based on the recommendations of the assessment committee and the interview committee.

The main criterion for selection will be the research potential of the applicant and the above-mentioned skills. The successful candidate will then be requested to formally apply for enrolment as a PhD student at the PhD school of Science.
You can read more about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.

Questions
For specific information about the PhD scholarship, please contact the principal supervisor, Assistant Professor Isabelle Augenstein, Department of Computer Science, e-mail augenstein@di.ku.dk.

General information about PhD programmes at SCIENCE is available at http://www.science.ku.dk/phd.

 

 

APPLY NOW

Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.

Info

Application deadline: 01-12-2019
Department/Location: Department of Computer Science


In your application, please refer to Polytechnicpositions.com

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