Sr. Machine Learning Scientist

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Job description

Job Description

The successful candidate will function as a key member of NeuroPace's Applied AI Research group , interacting closely with clinical, research and engineering personnel. Responsibilities include clinical and device data analysis, machine learning model development and validation, deployment and maintenance of ML/AI models on the software production platform. They will support ad hoc analyses to address research, clinical, and engineering neuroscience questions, and contribute to new technology development.

Responsibilities

• Mine the large NeuroPace RNS dataset to identify patient-specific and cross-patient brain activity patterns.
• Perform AI/ML model development and validation.
• Build and maintain machine learning processing pipelines.
• Participate in developing techniques to enable manual labeling of large neuroscience datasets.
• Participate in IP development.
• Publish research in top-tiered ML and Neuroscience journals.
• Work well independently and in teams.
• Work well in fast-paced environments and in the presence of ambiguity.
• Work closely with software and electrical engineering teams.

Requirements

• PhD in CS/EE/BME or any engineering field with focus on Machine Learning and Data Science.
• 4+ years' post-doctoral work experience in industry or academia.
• Published ML/AI work in peer-reviewed journals and conferences.
• Strong programming skills in python.
• Database skills (SQL).
• Experience with signal processing tools and methods (numpy, scipy).
• Experience with machine learning methods such as clustering, feature selection, dimensionality reduction, and classification and regression models.
• Good understanding of data structures and algorithms.
• Experience with training and validating deep learning models (CNNs, sequence and attention-based models)
• Experience with Tensorflow and Keras, or Pytorch.
• Keen interest to stay up-to-date with latest developments in AI.
• Familiarity with version control tools.
• Self-starter, able to work with minimal supervision.
• Strong problem-solving skills.
• Great work habits. Proactively update team members on progress.
• Prior experience working on large neuroscience or health datasets is a plus