Research Fellow - Deep Learning

Qualifications

PhD or an equivalent degree in computer science, neuroscience, biomedical engineering, or related fields
Broad proficiency and experience with supervised and unsupervised machine-learning methods, expertise in building neural network architectures
Experience with neuroimaging data processing
Advanced programming skills (Python and/or Matlab), including deep learning packages (e.g., TensorFlow or Keras)
Knowledge and experience with cloud-based computational platforms (e.g., AWS)
Excellent verbal and written communication skills
Strong publication record and academic credentials
Ability to work effectively both independently and in collaboration with multiple investigators

Responsibilities

• Experimental data collection and processing
• Development and refinement of deep learning and other benchmark algorithms for predictive classification of dystonia and other related disorders
• Clinical translation and implementation of the developed algorithms and interactions with clinicians for their testing
• Establishment of new and fostering of existing collaborations
• Participation in the regulatory aspects of clinical translation and patenting
• Presentation of the results at the scientific meetings and publication of journal articles
• Mentoring junior staff

Skills

Broad proficiency and experience with supervised and unsupervised machine-learning methods, expertise in building neural network architectures
Experience with neuroimaging data processing
Advanced programming skills (Python and/or Matlab), including deep learning packages (e.g., TensorFlow or Keras)
Knowledge and experience with cloud-based computational platforms (e.g., AWS)

Benefits

The fellow will be highly competitive to pursue future opportunities in either academia or industry (pharma and biotech).

Pay

$70,000.00 - $71,750.00/Annual