The Neurorehabilitation group of the Instituto Cajal, Spanish National Research Council, is seeking highly motivated, full-time PreDoc researchers with experience in machine learning. The selected candidate will play a leading role in developing innovative and creative solutions in the context of European and National projects, covering the following topics:
- Analysis of a wide spectrum of brain & neural signals, e.g. EMG, EEG, and fNIRS in healthy subjects and people with neurological injuries (e.g. Parkinson’s Disease) during a great variety of motor tasks.
- Development of biomarkers of abnormal motor functions (based on inertial sensing measurements, eye tracking, voice recognition, bioelectrical signal activity) during gross and fine movements.
- Development of supervised and unsupervised machine learning models able to stratify, classify and predict the evolution of disease severity.
- A highly multidisciplinary context including experts from the engineering, clinical and neuroscientific backgrounds
- Intense collaboration with international groups involved in several ongoing European projects
- The opportunity to create and run new research lines and coordinate working teams
Available position will start on April 1, 2022. Salary will be decided on the candidate’s expertise. The successful candidate will be offered a fixed term contract for the duration of 1 year, renewable for additional 2 years.
– Previous experience on machine learning.
– Master degree in fields related to Engineering, Robotics or Computer Science.
– Proved experience in at least one of the following research fields: machine learning, deep learning, reinforcement Learning.
– Proficient programming skills
– Fluency in spoken and written English
– Ability to work in a team
– Experience in the human analysis (motion and/or neurophysiology)
– Experience in analysis of biological signals
– Experience in rehabilitation robotics
– Experience in writing grant applications and coordinating national/international projects
The deadline for applications is February 28.
If you are interested in applying, please send an email to: firstname.lastname@example.org, including your CV, graduate transcripts, letters of reference (preferred) or contact info of references, an electronic copy of MS. Thesis (if available); and a cover letter with a brief description of your motivation and qualifications.