This vacancy announcement has been extended until August 15, 2023.
The World Intellectual Property Organization (WIPO) is a specialized agency of the United Nations dedicated to developing a balanced and accessible international intellectual property (IP) system.
The Fellowship is hosted by the Advanced Technology Applications Center (ATAC), located in the Global Databases Division, is a research and development center focused on prototyping, developing, and providing a range of ML powered services and tools such as MT, speech to text and multimodal classification and similarity search. The tools created by ATAC are used both by internal and external clients for different purposes. ATAC is looking for candidates that could contribute to WIPO Translate, and potentially assist on other tools as well.
As part of the Patent Cooperation Treaty (PCT), WIPO disseminates patent applications through the public PATENTSCOPE search engine and provides English and French translations for the bibliographic data of every patent filed in the PCT system. However, in order to improve the accessibility of the patent documents, WIPO has developed its own machine translation (MT) toolkit, WIPO Translate, which allows to automatically translate whole patent documents. WIPO Translate is available for 13 languages: Arabic, Chinese, English, Finnish, French, German, Italian, Japanese, Korean, Polish, Portuguese, Russian, Spanish.
At WIPO we use machine learning (ML) techniques to create the best possible MT models out of our collection of word class data, with the goal of providing the most accurate translation possible in the patent domain while ensuring translation is quick enough for all users. WIPO Translate also provides models more fit for the purpose of translating non-patent documents.
This Fellowship provides an opportunity for a young professional to gain knowledge and experience in conducting and improving the different steps required to train MT models, such as data preparation, training, evaluation, and deployment to production, using state-of-the-art MT frameworks such as the Marian NMT toolkit. In addition, the candidate will assist the team with other natural language processing (NLP) tasks such as classification, summarization, and text generation.
(a) Reporting Lines
The Fellow shall work under the supervision of the Technical Support Officer, in close collaboration with the rest of the ATAC team.
2. Duties and responsibilities
The Fellow will be required to perform the following principal duties:
I) Neural Machine Translation (NMT)
a. Make the best use of state-of-the-art NMT frameworks such as Marian NMT
b. Run, maintain and improve pipelines for data processing, data augmentation, domain modelling, model training and evaluation
c. Use language and domain aware techniques such as data augmentation, use of placeholders and factored models to annotate, pre-process, and post-process our data
d. Leverage both industry-standard and state-of-the-art tools, frameworks, and architectures to create the best possible NMT models
II) MT quality estimation
a. Compare different MT models using state-of-the-art metrics
b. Use feedback from human evaluation to further improve our engines, and introduce new automatic metrics to capture the feedback
c. Help in developing further quality estimation metrics for our MT models
III) Integration and deployment of MT and NLP tools
a. Work on different tools and interfaces to consume MT: graphical user interfaces and APIs, targeting segment, paragraph, and document level translation, and supporting different formats such as plain text, XML and HTML
b. Deploy WIPO Translate on different environments, such as local servers, cloud servers and containers
IV) Develop methods to collect and clean training data
a. Have knowledge of techniques and frameworks to filter, clean and align documents, both for patent documents and other kinds of documents such as meeting proceedings
b. Work on data augmentation and combining various sources of data, such as in- and out-of-domain corpora, synthetic data, and human translations
c. Define workflows for updating NMT models using newly published documents using techniques such as incremental training, online training, and domain adaptation
3. Requirements
a) Education:
Essential: MSc in computer science in the fields of MT, computational linguistics, or related fields.
Desirable: PhD in computer science in the fields of MT, computational linguistics, or related fields.
b) Experience:
Essential: At least two years of experience in the field of ML. Relevant R&D projects or PhD may be considered as experience.
Desirable: At least two years of experience in NLP.
c) Languages:
Essential: either excellent knowledge of written and spoken English, or excellent knowledge of written and spoken French and good knowledge of English.
Desirable: knowledge of other official languages of the United Nations (Arabic, Chinese, Spanish, Russian and French), or of the other languages of the Patent Cooperation Treaty (Japanese, Korean, Portuguese and German) will be considered an asset.
d) Specific skills and competencies:
Essential:
o Prove extensive knowledge of deep learning architectures focused on text processing, both sequence to sequence and regression, such as RNN and transformer, along with popular implementations such as Marian NMT or the transformers library
o Strong programming skills, preferably in Python and Java
o Familiarity with Unix/Linux environments.
Desirable
o ML techniques: Neural Networks, Naive Bayes, SVM, Knn, EM, ANNs, etc.
o Programming and scripting languages: Python, Java, bash, Perl
o Web technologies: tomcat, JavaScript, angular, gunicorn, nginx
o Databases and data storage: MySQL, Redis, Lucene/Solr, ElasticSearch
o Administration of Debian and RHEL setups
o DevOps: version control systems (git, svn), build tooling, and deployment strategies both in local and cloud servers and containers
o Excellent writing skills for technical documentation, administration guides and user guides in English
o Scientific publications or significant contributions to open-source projects will be an advantage
4. Organizational competencies
1. Communicating effectively.
2. Showing team spirit.
3. Demonstrating integrity.
4. Valuing diversity.
5. Producing results.
6. Showing service orientation.
7. Seeing the big picture.
8. Seeking change and innovation.
9. Developing yourself and others.
5. Terms and conditions
a) Term of fellowship: A fellowship may be granted for a period of up to 12 months. The contract may be extended one or more times, provided that the maximum cumulative length of the fellowship does not exceed a period of three years.
b) Anticipated Start Date: September 15, 2023.
c) Location: WIPO Headquarters, Geneva, Switzerland.
d) Stipend is set in accordance with the level of qualifications and experience of the Fellow (stipend starts from 6,000 CHF monthly and may vary up to maximum 7,000 CHF monthly). Details are available on request.
e) Travel expenses: WIPO shall contribute towards the cost of the fellow’s travel on engagement and separation from service. If necessary, WIPO may provide assistance in obtaining an entry visa to Switzerland. (if applicable)
f) WIPO provides medical and accident insurance coverage during the course of the fellowship.
g) WIPO will request a “carte de légitimation” for the Fellow, which serves as a residence and work permit, from the Permanent Mission of Switzerland to the United Nations Office and to the other international organizations in Geneva. Family members of the Fellow are not eligible for a “carte de legitimation.”(if applicable)
h) Tax and social security: Fellows shall be solely responsible for meeting any taxation and social security obligations that may arise directly or indirectly from their contract with WIPO. (if applicable)
Additional information
Fellows are not staff members of WIPO and the position does not lead to any employment rights and entitlements beyond the terms of the fellowship.