About this role
Have you recently completed or expect very soon an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering or a closely related area? Are you interested in carrying out research on NLP during the next years? Are you excited to spend a part of your life in a pleasant city in the heart of the Italian Alps?
WE ARE LOOKING FOR YOU!!!
The Human Language Technology – Machine Translation (HLT-MT) group at Fondazione Bruno Kessler (Trento, Italy) in conjunction with the the ICT International Doctorate School of the University of Trento is pleased to announce the availability of the following fully-funded PhD position in Machine Translation.
TITLE: Flexible Machine Translation
DESCRIPTION:
Machine Translation (MT) has become reliable enough to concretely support the daily work of professional translators. In computer-assisted translation, machines allow humans to translate faster. In the same framework, human feedback should allow machines to translate better. This objective can be pursued in different ways, for instance by injecting knowledge about how specific segments (words, phrases, sentences) should be translated. But what about the relation between such segments and the world they refer to and evoke? For instance, what does a human correction of “accept” into “ratify” tell us about the domain and register of the original sentence? And what does it tell us about the proper translation of terms like “home” (“domicile”), “tell” (“notify”), “pay” (“indemnify”) appearing in the same legal document? To answer these questions, a smart use of human feedback should not only focus on local translation/correction patterns, but also on inference and projection mechanisms to abstract from them. This grant will be offered to students willing to take the challenge by combining research on statistical machine translation, machine learning and distributional semantics in a single “flexible MT” framework.
Job Description
The first year of the PhD is mainly devoted to the acquisition of scientific knowledge at both basic and high level. During the second year the PhD candidate will deepen his/her scientific knowledge and starts to establish his/her thesis work, identifying the objectives and research activities to be developed within the thesis. During the third year, the PhD candidate will focus on his/her personal contribution to the state-of-the-art on the chosen research problem and/or to the development of the proposed technological innovation. The research activity of the PhD candidate will be closely related to EU projects. This will allow the PhD candidate to develop collaborations with other researchers participating in these research projects and it may also allow him/her to spend part of his research activity at partner laboratories, both in the academia and in the industry. The PhD candidates have to pass the selection of the ICT Doctorate School to be enrolled as PhD students.
Working Environment
The doctoral student will be employed at the HLT-MT group at Fondazione Bruno Kessler, Trento, Italy. The group (about 15 people including staff and students) has a long tradition in research on machine translation and is currently involved in several H2020 European projects such as QT21, Cracker and MMT. Former students are nowadays employed in leader IT companies in the world.
Benefits
Fondazione Bruno Kessler offers an attractive benefits package, including a flexible work week, full reimbursement for conferences and summer schools, competitive salary, an excellent team of supervisors and mentors, help for housing (and partial reimbursement), full health insurance, possibility of Italian courses, sporting facilities.
Company:
FBK
Qualifications:
The ideal candidate must have recently completed or expect very soon an MSc or equivalent degree in computer science, artificial intelligence, computational linguistics, engineering or a closely related area. In addition, the applicant should
Have a strong interest in Machine Translation
Have a strong background in statistics, probability theory and machine learning
Have excellent programming skills in at least one of the following languages: C, C++, or Java
Enjoy working with real-world problems and large data sets
Enjoy working in a closely collaborating team
Language requirements:
Good knowledge of written and spoken English
Educational level:
Master Degree