The School of Informatics, University of Edinburgh, invites applications for a Research Associate position within the Statistical Machine Translation group www.statmt.org/ued/ . This position is full-time and fixed term, but with the possibility of extension. The position advertised will cover work relating to a combination of research and innovation projects.

The successful candidate will be expected to work closely with project partners across the EU to develop, integrate and adapt the latest research in Statistical Machine Translation to fulfil project obligations. A significant part of the work will be developing and applying neural network language models and translation models, in order to leverage their ability to deliver compact, state-of-the-art models.

The post is available from 15th June 2015 for 12 months (with the possibility of extension).

(1) Job Details

Job title: Research Associate
School: School of Informatics
Line manager: Principal Investigator

(2) Job Purpose

The successful candidate will be expected to work on both an EU H2020 innovation action, and on a research collaboration with an industrial partner. The innovation action is MMT (Modern Machine Translation). The goal of MMT is to deliver a large-scale commercial translation infrastructure based on a new open-source distributed MT architecture. The collaboration with an industry partner is focussed on integration of the latest neural network techniques into state-of-the-art machine translation systems.

(3) Representative Work Activities

In general, the work activities associated with the post are to support the Principal Investigator of a specific project in achieving the goals of the project, under his or her direction.

• Undertaking a specific role in the research project under supervision
• Taking responsibility for some elements of the planned research
• Planning and carrying out a work programme appropriate to the research activity
• Developing own research portfolio in related areas
• Contributing to the writing of research grants
• Contributing to dissemination and publication of personal and/or research teams findings as appropriate.

(4) Planning and organising

The post holder will have to agree a general plan of research with the Principal Investigator and progress will be monitored at pre-scheduled meetings.

(5) Problem Solving

The problems to be faced are purely scientific and the post holder will supply the detailed expertise for delivering a solution. They will be expected to achieve this under instruction by and with advice from the Principal Investigator and other academic and senior research staff.

(6) Decision making

The post holder will determine the specific techniques and approaches to be used in the course of the research, in agreement with the Principal Investigator.

(7) Key contacts/relationships

The post holder will principally interact with the Principal Investigator and other project staff and students. More generally, the post holder will discuss the work, and other questions of scientific interest, with other members of the project at other sites and with other members of the School of Informatics. The post holder will be expected to represent the University externally, by presenting their work at specialist meeting or workshops in the relevant research area. They may also be required to provide advice and support to relevant students.


University of Edinburgh


You should have the following:
– PhD (or near completion) or equivalent experience in Computer Science, Artificial Intelligence, or a related discipline
– Background in statistical machine translation, machine learning or natural language processing
– Strong programming skills, ideally including C++

It would be desirable for you to also have the following:
– Experience with the Moses toolkit including a good understanding of SMT decoder internals
– Experience with neural network models for NLP
– Good publication record

Specific requirements:

2 months, with the possibility of extension

Educational level:

Ph. D.

How to apply:

Please mention NLP People as a source when applying


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