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Position Summary

The Chappell and Silberg Lab in the Department of BioSciences are looking to hire a Postdoctoral Research Associate in the field of synthetic biology.

They are seeking an innovative and collaborative postdoctoral scholar to develop a new class of programmable, synthetic RNA-based therapeutics to address global health infectious disease challenges within microbial consortia. This project will involve the development of synthetic RNA using high-throughput approaches, the testing of those RNA within microbes that cause disease in the context of complex microbial consortia, and the application of machine learning to develop design rules for personalized medicine. Within this design-build-test-learn cycle, this position will focus on resolving design rules for synthetic RNA and applying these rules to create automated design algorithms. They will work collaboratively with experts in the testing and building of synthetic RNA. Additionally, this project seeks to create a modular RNA technology that can be rapidly translated to the clinic, and it will involve a team project that includes a clinician with expertise in human microbial-pathogens and pathobionts.

The ideal candidates will have training in computer science, statistics, data science, synthetic biology, biomolecular engineering, chemical engineering, biochemistry, microbiology, and related disciplines who are passionate about leading interdisciplinary projects in this space.

The Chappell (chappell-lab.org) and Silberg (silberglab.org) labs provide a supportive environment and are committed to training the next generation of synthetic biology leaders. Their labs are embedded within a highly collaborative community of synthetic biologists at Rice University (sspb.rice.edu), which continues to grow infrastructure in this intellectual space.

Informal inquiries can be made by providing Drs. Chappell ([email protected]) and Silberg ([email protected]) a cover letter describing your previous research and your interest in our lab, and a CV with names and contact information for references

Essential Functions

Specific research objectives include:

• Computationally designs synthetic biomolecules that exhibit cell-selective functions in consortia
• Establishes design rules for synthetic biomolecules with desired consortia scale functions using machine learning
• Creates and refines algorithms for the automated design
• Collaborates with other team members to support the building and testing of biomolecular libraries
• Collaborates with clinicians to support studies in patient-derived pathogens

Specific scientific duties include:

• Documents, analyzes, and maintains research data
• Assists with proposal development to obtain research funding
• Mentors, oversees, and/or trains junior research team members
• Publishes and presents research findings
• Supports project management and collaboration across institutions or disciplines
• Designs and implements research protocols; adapts new procedures, methods or instrumentation relative to research procedures
• Provides academic services to the department (i.e., teaches a course)
• Performs all other duties as assigned

Required Qualifications and Skills

• Ph.D in synthetic biology, biomolecular engineering, chemical engineering, biochemistry, microbiology, and related disciplines or related field

Specific research skills and expertise:

• Technical expertise in aspects of the Design, Build, Test, and Learn cycle of synthetic biology
• Technical knowledge in computational systems or synthetic biology
• Technical proficiency in analyzing big data computationally, such as deep sequencing

Specific technical skills and knowledge:

• Excellent verbal and written communication skills, as well as oral presentation skills
• Organization and time management skills
• Knowledge of modern research methods, data collection, and analyses
• Knowledge of the principles and techniques of the subject discipline
• Writes scholarly papers based on ongoing research and submits them to journals for publication
• Able to work in a collaborative environment
• Able to work independently and professionally with minimal supervision and direction

Preferred Qualifications

Specific research skills and expertise:

• Technical knowledge in analyzing deep sequencing data
• Technical knowledge in evolutionary analysis of biological sequence data
• Technical knowledge in applying machine learning to develop quantitative models
• Technical knowledge of writing and applying computer algorithms (e.g., Python, R, Matlab)

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