Post-Doctoral Researcher

Scripps College • Claremont, CA

1d • Onsite

About The Position

Working with Professor Sarah Marzen, the Post-Doctoral Researcher will serve in an advanced professional research capacity to conduct original scholarly and scientific research relating to the engineering of hybrid adaptive networks. The Researcher will routinely need to apply advanced knowledge in physics, applied mathematics, biophysics, scientific computing, and related fields.

Requirements

• Ability to demonstrate excellent written and verbal communication skills, and meticulous attention to detail.
• Ability to interact with faculty, staff, and other members of a college community.
• Ability to process large amounts of information and manage multiple deadlines efficiently and accurately.
• Excellent computer skills, preferably with Microsoft Office (Excel and Word), LaTeX, and Python or some other scientific computing software.
• Excellent communication skills, including writing scientific papers and giving scientific presentations.
• Excellent analytic skills, including proficiency with several areas of mathematics such as dynamical systems and information theory.
• Independent judgment exercised to produce ready-to-go drafts of scientific papers and scientific presentations.
• Demonstrated ability to exercise discretion and independent judgment in conducting advanced scientific research and in preparing near-final scientific papers, technical analyses, and professional presentations.
• Ph.D. in physics or a closely related scientific field is required.
• Advanced knowledge in a field of science or learning customarily acquired through a prolonged course of specialized intellectual instruction.

Nice To Haves

• Knowledge of Workday is a plus.
• Demonstrated research experience in mathematical modeling, theoretical or computational science, neural networks, biophysics, applied mathematics, or related disciplines is strongly preferred.

Responsibilities

• Independently design and perform advanced analytical and computational research to benchmark, model, calibrate, and evaluate the performance of hybrid adaptive networks.
• Develop, test, and refine original theories, methodologies, neural network topologies, and engineered dynamics to improve the design and predictive performance of hybrid adaptive networks.
• Collaborate with internal and external research partners, including University of Maryland collaborators on a large MURI project, to formulate research objectives, analyze complex scientific issues, compare engineered and optimal neural network topologies, and develop new topologies for practical implementation.
• Provide research guidance and technical direction to undergraduate lab assistants, research staff, and other junior collaborators in connection with ongoing scientific projects.
• Prepare publication-quality manuscripts, research reports, presentations, and open-source computational tools that communicate original scientific findings for leading journals and professional audiences in biophysics, applied mathematics, and related disciplines.
• Actively support the College’s Principles of Community and Institutional Values in the performance of professional responsibilities.

Benefits

• benefits eligible

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: Ph.D. or professional degree
• Number of Employees: 11-50 employees