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Research Scientist in Computational Neuroscience and Machine Learning
hace 2 meses
We are seeking a highly skilled Research Scientist to join our team at Telefónica, S.A. in the field of Computational Neuroscience and Machine Learning. As a key member of our research team, you will have the opportunity to propose and develop research ideas individually, as well as jointly with members of the research team and Telefonica at large.
Key Responsibilities- Design and conduct research projects that bridge neuroscience and artificial intelligence (e.g., BCI).
- Develop computational models of neural systems using deep learning, reinforcement learning, and/or neuromorphic AI techniques inspired by biological neural networks.
- Design, plan and execute in a timely manner lab-based, controlled experiments for data acquisition and subsequent analysis.
- Propose and develop disruptive research ideas for advancing the state of the art in the respective field of their expertise.
- Create and lead long-lasting and high-value synergies with academic institutions, industrial partners, customers, and government agencies.
- Promote the dissemination of research results via high-quality publications and demonstrations in major venues worldwide.
- Partner with business (and other Telefonica) units to ensure the successful exploitation of research outputs.
- Supervise interns and collaborate openly with other researchers, as well as other Telefonica employees.
- Pursue funding opportunities for personnel and/or equipment and/or research visits, via proposal writing and submission for National and/or European and/or International competitive grants.
- Ph.D. in Computational Neuroscience, Computational Psychology, Physics, or any related fields.
- Strong domain knowledge and prior experience in Machine Learning (with a specialization in Deep Learning, Reinforcement Learning, and/or Neuromorphic AI).
- Some expertise and prior experience with controlled experimentation methods and neuro-physiological signal processing (EEG, fNIRS, EDA), as well as user studies (online and offline), A/B testing and self-report methods is desirable.
- Knowledge and prior experience with tools (e.g., methodologies, software, testbeds, models, etc.) related to the above areas.
- Proven track of strong research output (e.g., publications, patents).
- Strong verbal, visual, and written communication skills.
- Ability to work in a highly dynamic and interdisciplinary environment.
