-- Apologies for cross-posting.
-- 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 Speech Translation 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 Machine Translation <https://mt.fbk.eu/> (MT) group at Fondazione Bruno Kessler (Trento, Italy) in conjunction with the ICT International Doctorate School of the University of Trento <https://ict.unitn.it/> is pleased to announce the availability of the following fully-funded Ph.D. position in Speech Translation. TITLE: Flexibility and Robustness in Speech Translation DESCRIPTION: The need to translate audio input from one language into text in a target language has dramatically increased in the last few years with the growth of audiovisual content freely available on the Web. Current speech translation (ST) systems are now required to be flexible and robust enough to operate in different application scenarios and diverse working conditions. On one side, the industry calls for key features like real-time processing, domain adaptability, extended language coverage, and the capability to adhere to application-specific constraints (e.g. length or lip-synch constraints in the subtitling and dubbing scenarios). On the other side, society calls for new efforts towards inclusiveness with respect to specific categories and groups (e.g. gender-sensitivity, customization to the needs of impaired users). Both dimensions (industry and society) face the orthogonal challenges posed by the variability of audio conditions (e.g. background noise, strong speakers’ accent, overlapping speakers). The objective of this Ph.D. is to advance the state of the art in speech translation to make ST flexible and robust to these and other factors. CONTACT: [email protected], [email protected] COMPLETE DETAILS AVAILABLE AT: https://iecs.unitn.it/education/admission/call-for-application IMPORTANT DATES: The deadline for application is August 31, 2021, hrs. 04:00 PM (CEST) Potential candidates are strongly invited to contact us in advance for preliminary interviews. Precedence for interviews will be given to short-listed candidates that will send us a complete CV via email ( [email protected], [email protected]) by August 20, 2021. Candidate profile 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 and Speech Translation - Have a strong background in deep learning and machine learning, in general - Have excellent programming skills in Python and experience in PyTorch - Enjoy working with real-world problems and large data sets, in particular in exploring the biases in data and algorithms - Good knowledge of written and spoken English - Enjoy working in a closely collaborating team Working Environment The doctoral student will be employed at the MT group at Fondazione Bruno Kessler, Trento, Italy. The group (about 10 people including staff and students) has a long tradition in research on machine and speech translation and is currently involved in several projects. Former students are nowadays employed in leading 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, a competitive salary, an excellent team of supervisors and mentors, help for housing, full health insurance, the possibility of Italian courses, and sporting facilities. Further Information For further information about the position, please contact Matteo Negri ( [email protected]) and Marco Turchi ([email protected]). Best Regards, Marco Turchi
_______________________________________________ Mt-list site list [email protected] https://lists.eamt.org/cgi-bin/mailman/listinfo/mt-list
