Postdoctoral Research Associate

University of Arizona | Academic | Tucson, Arizona | More →

The Kacar Astrobiology Group ( at the University of Arizona in the Department of Molecular and Cellular Biology is looking to hire a Postdoctoral Researcher to explore the origins of early life, with an emphasis on the early evolution, reconstruction of molecular evolutionary landscapes, and topological features of biosynthetic networks. Our lab works at the interface of molecular evolution, synthetic biology, genome engineering, biochemistry, molecular biology and astrobiology and is host to one of the NASA Interdisciplinary Consortia for Astrobiology Research centers dedicated to understanding early Earth biology and evolution. This position is fully funded.

Primary responsibilities of the candidate:
• Use machine learning and artificial intelligence algorithms to compare biotic to abiotic chemical networks and assess whether the behavior of these chemical systems are comparable in informatic and semantic terms
• Coding proficiency to develop new analytical tools and techniques in service to above goals; primarily using Python.
• Work collaboratively with IBM Research – Almaden (remotely, if required by pandemic restrictions)
• Mentor and train graduate students, undergraduates and other laboratory fellows as needed.
• Attend and present during weekly laboratory and astrobiology group meetings, maintain detailed annotated code/data on GitHub and internal databases, follow all the safety and laboratory regulations
• Assist with grant writing/formatting, manuscript preparation/submission/proof reading
• Provide targeted research and background reading, as well as assistance with presentation preparation as needed.
• Data analysis and figure generation
• Additional duties may be assigned.

Required qualifications:
PhD. in Chemistry, Theoretical/Computational Chemistry, Machine/Deep Learning, Physics, Mathematics or Software Engineering or related disciplines.
Demonstrated work experience in network simulation or similar fields with an emphasis on theoretical or applied network analysis techniques.
Good organizational skills and detailed software annotation training are required.

Preferred qualifications/experience:
Experience in computational biology and/or molecular evolution is a plus.
Work history that demonstrates experience in establishing relations between the structure/dynamics of abiotic chemical reaction networks and observable biosynthetic, information processing and semantic relationships.
Familiarity and practical experience with modern statistical learning approaches, including generative modeling and/or reinforcement learning
Proactive approach to research responsibilities
Strong leadership and writing skills, and demonstrated mentorship

Additional information: Competitive salary with benefits, Highly encourage Under-represented Groups to apply

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