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Scientist I/II Machine Intelligence

Department: 2230 - Modeling and Theory
Location: Seattle

Scientist I/II Machine Intelligence

Our mission at the Allen Institute is to advance our understanding of how the brain works in health and disease. Using a team science approach, we strive to discover how the brain implements fundamental computations through the integration of technological innovation, cutting-edge experiments, modeling, and theory.

Understanding the brain constitutes one of the foremost scientific challenges we face.  An important aspect of understanding cortical function is to connect the anatomical construction of neural networks with the physiological response characteristics as well as the overall computation performed by the circuit.  This effort will draw upon techniques and knowlege from machine learning, computer science, and biology.

We seek an exemplary scientist to join our efforts in understanding the cortical basis of computation.  The successful candidate will demonstrate a facility with modern machine learning approaches as well as a strong theoretical foundation in statistics and machine learning.  The ideal candidate will also have a strong knowledge of neuroscience, both experimental and computational, and reinforcement learning. 

The successful candidate will pursue the construction and analysis of anatomically constrained, task-trained artificial neural network models of cortical function, with the ultimate aim of understanding the computational strategies and function of cortex.  They will perform data analysis on neurophysiological data and work closely with experimentalists to understand our data. 

Essential Duties

  • Develop and analyze task-trained, anatomically constrained artificial neural network models.
  • In close collaboration with experimentalists and other analysts, work as a team member to analyze large-scale neurophysiological activity.
  • Contribute scientific ideas based on the analysis results.
  • Develop and maintain computational and associated software tools.
  • Publish/present findings in peer-reviewed journals and at scientific conferences.
  • Maintain clear and accurate communication with supervisor and other team members.
  • Communicate effectively and appropriately to the research community inside and outside the organization.

Required Education and Experience

  • PhD degree in Computer Science, Computational Neuroscience, or related discipline.
  • 0-2 years of post-doctoral experience.
  • Strong computational/data analysis skills; ideally programming in Python.
  • Familiarity with PyTorch or TensorFlow.
  • Track record of scientific excellence and independent thinking.

Preferred Education and Experience

  • Excited about team science and open science.
  • Ability to meet aggressive timelines and deliverables in a collaborative environment.
  • Excellent written and verbal communication skills.
  • Experience in systems neuroscience (especially in vivo neural measurements and/or sensory neuroscience).
  • Excellent organizational skills and attention to detail.

Physical Demands

  • Fine motor movements in fingers/hands to operate computers and other office equipment; lab equipment

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.

 

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