Research Fellow - Deep Learning
Core
Developing machine-learning algorithms for automatic diagnosis of dystonia, predicting risk of dystonia development, and assessing treatment efficacy using brain MRI datasets.
Role type
Postdoctoral Fellow in Deep Learning
Builds
DystoniaNet platform for clinical use in movement disorder diagnosis
Domain
Healthcare / Neuroimaging / Deep Learning
Deliverable
production ML models
Required skills
supervised and unsupervised machine-learning methods, neural network architecture design, neuroimaging data processing, Python, TensorFlow or Keras, cloud-based computational platforms
Preferred skills
academic credentials, strong publication record
Technologies
Python, Matlab, TensorFlow, Keras, AWS
Responsibilities
Experimental data collection and processing, development and refinement of deep learning algorithms for predictive classification, clinical translation and implementation of algorithms, establishment of collaborations, participation in regulatory aspects and patenting, presentation of results at scientific meetings and publication of journal articles, mentoring junior staff
Seniority
Postdoctoral, research-focused IC