Staff Scientist

Department
 

PME Chevrier Lab

About the Department
 

The Pritzker School of Molecular Engineering (PME; https://pme.uchicago.edu/) was established in May 2019 and evolved from the Institute for Molecular Engineering, which was founded in 2011. The PME integrates science and engineering to address global challenges from the molecular level up. The PME’s rigorous academic and research programs are made possible through the University of Chicago’s unique partnership with Argonne National Laboratory. The Pritzker School of Molecular Engineering is the first new school at the University of Chicago in three decades and the first school in the nation dedicated to molecular engineering. In the next phase of growth as a School, the PME will continue to expand its team of world-class faculty researchers and empower students from diverse backgrounds to collaborate with faculty in cutting-edge facilities. The PME aims to bring solutions for urgent societal problems to the forefront, while training the next generation of scientific leaders and entrepreneurs.

Job Summary
 

The Chevrier Lab at the Pritzker School for Molecular Engineering is looking for a highly motivated Computational Scientist to work closely with faculty and researchers at the University of Chicago. The successful candidate will play a key role in characterizing and engineering the immune system in health and disease by working with the Chevrier Lab and in collaboration with researchers and clinicians at the University of Chicago and beyond. Emphasis will be to (i) generate new biological insights by developing new approaches to analyzing large-scale and high-throughput data (e.g., next-generation sequencing, high-throughput screening), (ii) maintain, upgrade, and train users on existing pipelines in the lab, and (iii) develop new pipelines as needed.

Responsibilities

• Facilitates and promotes advanced technical/scientific research projects, including simulations and data analysis. Recognizes the need for innovation and develops or incorporates advances in research concepts to help disseminate results.
• Develops, applies, documents, and maintains computational tools, both for use and to support analysis by biologist colleagues without formal computational training. Critically evaluates computational solutions.
• Develops customized computational solutions supporting new kinds of assays and experiments. Understands the analytical needs of new experiments, working closely with wet-lab experimental biologists.
• Implements and optimizes successful algorithms and methods to be shared for use by the broader community.
• Develops figures and reports that provide transparency into the data quality and characteristics and automate the production of such reports as routine components of computational analysis pipelines.
• Reports data to supervisor and team, attends team meetings to share results, plans projects and experiments, and ensures that projects support current team goals.
• Maintains and organizes computational infrastructure and resources.
• Contribute to the generation of protocols, publications, and intellectual property.
• Reviews laboratory protocols and training on new techniques. Manage complex data sets for research.
• Trains new laboratory personnel.
• Performs other related work as needed.

Minimum Qualifications
 

Education:

Minimum requirements include a PhD in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications

Education:

• Doctoral degree in computer science, computational biology, bioinformatics, quantitative science, or related field.

Experience:

• A minimum of three years of significant work experience after the doctorate; postdoc experience.
• Possess experience in a research laboratory, preferably in an independent project.
• Conduct wet or dry lab work in a research laboratory, preferably in an independent project.
• Practical experience in data analysis, preferably in an independent project in an academic research laboratory setting.
• Background in statistics and machine learning.

Technical Skills or Knowledge:

• Basic knowledge of biology or immunology or inclination to acquire such knowledge.
• Knowledge of SLURM or other job scheduler, and/or bioinformatics tools.
• Fluency in Unix, standard bioinformatics tools (Python, R, or equivalent), and a programming language (C/C++, Java).
• Strong computer skills, including calendaring, doc