POST- DOCTORAL POSITION
Computational motor learning and rehabilitation
We are seeking a highly qualified and motivated individual for a post-doctoral position in computational motor learning and rehabilitation at Tsukuba University, about 45 minutes from Tokyo. The post-doctoral fellow will work closely with an interdisciplinary team of neuroscientists, engineers, physical therapists, and rehabilitation physicians. The primary focus of this position will be at the intersection of computational motor control, motor learning, neuro-imaging, and rehabilitation. The candidate will work with both Dr. Jun Izawa from Tsukuba University and with Dr. Schweighofer from the University of Southern California in Los Angeles. The position is initially for 1 year, renewable based on progress.
The ideal candidate should possess:
• A PhD in biomedical, computer science, electrical engineering, neuroscience, or a related field.
• Knowledge of control theory and mechanical modeling.
• Good level in advanced statistics and/or machine learning (with R or Matlab).
• Good knowledge, or at least strong interest, in Neuroscience.
• Experience collecting motion capture and/or other biomechanical measurements from human subjects.
• Experience, or at least strong interest, in working with patients with neurological disorders.
• Evidence of scholarship; e.g. peer-reviewed publications.
• Demonstrated ability to work independently and as a member of a multidisciplinary team.
• Interest in living in Japan and integrating in a largely multi-cultural environment.
The fellow will be joining a state-of-the-art human informatics laboratory which includes a 3D motion capture system, robotic manipulanda for reaching and for finger movements, and wireless surface EMG system. The expected start date is April 2017. To apply for this position, please send a CV and the names and contact information of three references to Dr. Jun Izawa and Dr. Schweighofer via email izawa@emp.tsukuba.ac.jp and schweigh@usc.edu. Applications will be accepted until the position is filled.
Computational motor learning and rehabilitation
We are seeking a highly qualified and motivated individual for a post-doctoral position in computational motor learning and rehabilitation at Tsukuba University, about 45 minutes from Tokyo. The post-doctoral fellow will work closely with an interdisciplinary team of neuroscientists, engineers, physical therapists, and rehabilitation physicians. The primary focus of this position will be at the intersection of computational motor control, motor learning, neuro-imaging, and rehabilitation. The candidate will work with both Dr. Jun Izawa from Tsukuba University and with Dr. Schweighofer from the University of Southern California in Los Angeles. The position is initially for 1 year, renewable based on progress.
The ideal candidate should possess:
• A PhD in biomedical, computer science, electrical engineering, neuroscience, or a related field.
• Knowledge of control theory and mechanical modeling.
• Good level in advanced statistics and/or machine learning (with R or Matlab).
• Good knowledge, or at least strong interest, in Neuroscience.
• Experience collecting motion capture and/or other biomechanical measurements from human subjects.
• Experience, or at least strong interest, in working with patients with neurological disorders.
• Evidence of scholarship; e.g. peer-reviewed publications.
• Demonstrated ability to work independently and as a member of a multidisciplinary team.
• Interest in living in Japan and integrating in a largely multi-cultural environment.
The fellow will be joining a state-of-the-art human informatics laboratory which includes a 3D motion capture system, robotic manipulanda for reaching and for finger movements, and wireless surface EMG system. The expected start date is April 2017. To apply for this position, please send a CV and the names and contact information of three references to Dr. Jun Izawa and Dr. Schweighofer via email izawa@emp.tsukuba.ac.jp and schweigh@usc.edu. Applications will be accepted until the position is filled.