You may have enjoyed reading about bots, artificial intelligence, machine learning,
digital assistants, systems that support doctors, teachers, customers and help people.
Then, you would like to consider taking a front row seat and join the research team
that has been training intelligent machines and evaluating AI-based systems
for more than two decades, collaborating with best research labs in the world and
experimenting in the real-world.
Name : Multimodal people monitoring using sound (and vision)
Type : Postdoc
Description : The Idiap Research Institute together with Swiss Center for Electronics and Microtechnology (CSEM) invite applications for a post-doctoral position in research and development for multimodal people monitoring.
The position is funded for one year by Idiap (with a possible extension depending on his/her performance)
The Idiap Research Institute together with a global industry partner, leader in Consumer Electronics, invite applications for two post-doctoral positions in speech and speaker recognition for HMI devices. The positions are funded for two years by the Swiss Commission for Technology and Innovation (CTI), enabling a collaboration between Idiap and an innovative product company.
The Analyst will be a part of team who would be a brain behind building a new voice assistance or Artificial intelligence recognition Apps (like Siri/ Cortana/ Google assistance) for one of our world class mobile customer.
We need Bright Fresher’s who would help us to integrate the NLU engine for upgrade, who plan and execute feature upgrade cycles, who apply regression testing on NLU engine and understand the regression failure cases.
Three Postdoctoral Researchers/Project Researchers (Speech processing and deep learning)
The University of Eastern Finland, UEF, is one of the largest multidisciplinary universities in Finland. We offer education in nearly one hundred major subjects, and are home to approximately 15,000 students and 2,500 members of staff. From 1 August 2018 onwards, we’ll be operating on two campuses, in Joensuu and Kuopio. In international rankings, we are ranked among the leading universities in the world.
Manual operation of hearing assistive devices is cumbersome in various situations. With advances in machine learning and speech technology, voice interfaces due to their convenience will be widely deployed for hearing assistive devices and they can be personalized and offer richer functionalities. Hearing assistive devices are characterized by strict memory and computational complexity constraints and the fact that they are expected to operate flawlessly, even in acoustically challenging situations.