Identify, understand and deploy modern deep learning methodologies for the automation of translation and adaptation of medical information materials, as well other text processing automation tasks. Lead the implementation of such technology into our content authoring and production processes and systems. Key partner to NLP scientists in the Content and Innovation department in operations.
Key Result Areas
Identify and keep close to modern deep learning and artificial intelligence technologies that have the potential to help us automize key content tasks to localize books and electronic products in the international markets.
Identify the best modern technologies to automate translation and adaptation of medical information materials
Support research into the capabilities of deep learning based natural language processing machines to support other tasks in text mining, automatic extraction of knowledge, etc particularly in medical information.
Collaborate closely with C&I and IT development to build and train machines.
Lead development and training of translations engine to support translations between English and the core languages of Spanish, Portuguese, Japanese, Chinese, French, and German
Implement translation, extraction, and adaptation machines for use in our production content workflows, leading to significant cost and time savings in localization and preparation of clinical and educational content.
Project manage the Integration and adaption of new models into production systems
PhD or MSc in natural language processing, Artificial Intelligence, Computer Science, or related fields
Experience with applied Machine Learning and Natural Language Processing in industry
Experience working with deep learning pipelines in production environment
Proficient in any of the following deep learning technologies or libraries: CNTK, NLTK, SpaCy, Gensim, Scikit-learn, Keras, Torch, TensorFlow (or similar)
Previous work in one or more of the following fields: Information Retrieval, Knowledge Extraction, Question Answering, Machine Translation, Deep Learning
Experience working with, training, and evaluating machine translation systems is not a prerequisite, but will be considered as a very important and positive profile aspect for the role.
How to apply:
Please mention NLP People as a source when applying
A leading provider of science and health information, Elsevier partners with experts around the globe to develop world-class content, delivering it in ways that fuel discovery, drive innovation and improve health care. Our global community comprises over 7,000 journal editors, 70,000 editorial board members, 300,000 reviewers and 600,000 authors. They are scientists and clinicians; authors and editors, professors and students; information professionals and decision makers.
We are a global company headquartered in Amsterdam, employing more than 7,000 people in 24 countries. Elsevier's roots are in journal and book publishing, where we have fostered the peer-review process for more than 130 years. Today we are driving innovation by delivering authoritative content with cutting-edge technology, allowing our customers to find the answers they need quickly.