We are looking for research scientists with a deep passion for brain-machine interaction and a great understanding of the most recent machine learning approaches such as deep learning associated with biosignals-related challenges, to join our fast-growing multidisciplinary team. You will have the opportunity to contribute in creating a new generation of Brain Computer Interfaces (BCIs) fusing cutting-edge machine learning, neuroscience and embedded systems, applied across various projects with top level academic and industrial partners.
You will join a team of 10+ enthusiastic engineers, scientists and researchers
A full-time open-ended contract with paid vacation and sick days
High-end Linux laptop or workstation with root access
Informal working environment and a team of young motivated professionals with experts in different fields
Continuous learning by attending to company organized lectures and self-time to experiment
New top floor office close to the historical centre of the city
Lodging and relocation contribution to Parma (Italy) (some limitations may apply)We offer a competitive salary based on the experience and skills
• You will be responsible for the close-to-signals layers of the CAMLIN ML-based BMI architecture (signal acquisition, synchronization, denoising, low level feature extraction)
• You will contribute to the implementation on embedded platforms, both fog and edge, of cutting-edge ML-based models for signal treatment for BMIs.
• You will develop custom machine learning solutions for the rapid and robust cognitive control of real-world devices in naturalistic scenarios
• You will be involved in the writing of patents and scientific articles
• Master degree in Electrical Engineering, Computer Science, Physics, Mathematics, or other relevant fields + relevant work experience and/or PhD
• Proven sound experience with coding in modern programming languages (Python, C, C++ are essential) and SW development on embedded systems like Nvidia Jetson TX2, Raspberry PY, PULP processors, microcontrollers
• Solid experience with the treatment and analysis of multimodal biological signals (e.g., EEG, EMG, ECoG, eye gaze) in real time, and synchronization middleware like LSL
• Proven previous experience with Android programming
• Proven experience with Machine Learning frameworks like Tensor Flow, Keras, Scikit-learn and issues related to models downscaling on embedded platforms
• Team working capabilities and flexibility but also strong autonomy in working by objective
• Good oral and written English
• Feels at home with soldering station, electronic lab equipment, hardware hacking
• Feels the “need” to write high performance production quality code and builds elegant class structures, and feels at home with Git+JIRA+Confluence tools
• Enjoys optimizing algorithms for modern multi-core CPU with GPU embedded devices such Jetson TX2 and parallel multicore processors such as PULP. In other words, feels at home with cloud, fog, edge computing
• Has knowledge and previous experience in ROS (Robot Operating System).
• Is open minded and enjoys approaching complex problems with a multi-disciplinary approach