Allen Institute: Asst. Investigator – Computational Neuroscience/Machine Learning

Our mission is to accelerate the understanding of how the human brain works. Using a big science approach, we generate public resources, drive technological advances, and discover fundamental brain properties.

Allen Institute Company: Allen Institute
Location: Seattle, WA

Our mission at the Allen Institute for Brain Science is to accelerate the understanding of how the human brain works in health and disease. Using a big science approach, we generate useful public resources, drive technological and analytical advances, and discover fundamental brain properties through integration of experiments, modeling and theory.

The Assistant Investigator will act as a lead scientist in developing a machine learning program for classification and comparative analysis of the Allen Institutes neuroscience programs data. This work will include both problems of cell type classification including diverse data modalities such as transcriptome and synaptome, electro- and optical physiology, and light and electron microscopy morphological and connectivity data. By combining data from mouse, human, and developing and human embryonic stem cell approaches, we wish to use robust modern quantitative clustering tools to understand the spectrum from components to circuits to cognition, and ultimately what makes humans human.

Job Responsibilities:
  • Establish a group and key facility in the development and application of modern machine learning techniques to the understanding of neurobiological data.
  • Develop the methodology and techniques for the quantitative exploration of cell type characterization and classification.
  • Advise a group of scientists in developing these methods.
  • Work with experimentalists to understand their data and to suggest new experiments.
  • Compare model against electrophysiological and imaging data from in-house observator.
  • Seek and evaluate new cutting-edge technologies in related areas.
  • Publish/present findings in peer-reviewed journals/scientific conferences.
  • Present a periodic summary of progress to the research community within the organization.
  • Communicate effectively and appropriately with others inside and outside the organization.

Basic Qualifications:
  • Ph.D. in a physics, engineering, or computational discipline
  • 5 + years of postdoctoral working experience in computational neuroscience and machine learning
  • Extensive experience and technical knowledge of computational neuroscience, modeling and machine learning, including modeling networks of spiking neurons, deep learning, algorithms, hierarchical clustering
  • Strong knowledge of systems, cellular and molecular neuroscience

Apply online .