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Senior R&D Developer - Handwriting - Computer Vision

Nuance offers an exciting opportunity for a Senior Software Engineer - R&D to develop and improve handwriting recognition systems for the transformative automotive industry.

Research Intern

In this position, you will pursue cutting edge research aligned with Nuance’s long-term AI roadmap. The focus will be on developing or improving deep learning algorithms/models for application in natural language understanding and conversational AI systems.  

Senior Research Engineer - ASR/Deep Learning (Automotive)

You will contribute to the next generations of automatic speech recognition (ASR) for automotive applications on embedded platforms and on the cloud. As senior research engineer you will investigate and implement speech recognition algorithms focusing on the integration of the newest deep learning based techniques targetting continuously listening applications. As part of a strong research team, you will be able to contribute key innovations which advance the capabilities of AI and personal assistants in  automotive.

Research Application Scientist - Japanese NLU

As a Research Application Scientist you will support us in the R&D in natural language understanding (NLU) for Japanese. You will assist in all aspects of planning, developing and maintaining high-quality NLU systems for customers. The job includes new feature development, accuracy improvement, project maintenance, and language-targeted research for improvements.

The position can be filled in the following office locations: Aachen (Germany) or in Burlington, MA (US)

Responsibilities:

Principal Research Scientist - ML/DL/Speech Recognition (Automotive)

As a Principal Research Scientist you will do research into all aspects of speech recognition algorithms with the aim of optimizing accuracy. This will include research into algorithms to increase robustness to various acoustic conditions encountered in real-world data, as well as underlying modelling techniques.

This position can be filled in our office in Cambridge, UK.

Responsibilities:

Senior Research Scientist - AI and Machine Learning (Automotive)

The candidate is expected to contribute to cutting edge research in Artificial Intelligence and Machine Learning applications. The candidate is expected to develop and implement AI and Machine Learning prototypes and solutions for real world problems that are relevant to Nuance and its customers, including user modeling / preference learning, and inference.The candidate is expected to work/collaborate with other members of the group and across Nuance to successfully productize and deploy R&D outcomes.

The position is located in our office in Aachen, Germany. 

Postdoc Positions in Seismic Oceanography - Inversion

The selected candidate will work in the area of seismic data processing applied to the definition of water masses (seismic oceanography - Inversion). It will also act in the evaluation of the data received and in the preparation and realization of the cruises to obtain shallow seismic data in Brazilian waters and data analysis. It is expected to produce technical reports and scientific papers from the research group.

Requirements: Knowledge of signal processing and programming in computer language (eg MATLAB, Phyton or C ++). Knowledge in seismic inversion is desirable.

Postdoctoral Researcher

Immediate opening for a postdoctoral researcher in radionavigation and wireless communication systems at the Autonomous Systems Perception, Intelligence, & Navigation Laboratory (https://aspin.ucr.edu); University of California, Irvine (https://uci.edu).

Deputy Director

https://nato.taleo.net/careersection/2/jobdetail.ftl?job=190339&lang=en#.XKyV6uNspCw.gmail 

 

Deputy Director-190339

 

Primary Location

 Italy-La Spezia

NATO Body

 Centre for Maritime Research and Experimentation (CMRE)

Schedule

 Full-time

Euro (EUR) Yearly

Grade A.6

  

Postdoc position in auditory perception at Johns Hopkins University

Applicants are sought for a postdoctoral position on a project of auditory perception in complex listening environments. The project employs signal processing and computational models as well as experimental techniques (recordings of brain activity) to explore mechanisms underlying auditory scene analysis and their translation into smart audio technologies. 

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