The Pritzker School of Molecular Engineering at the University of Chicago is looking for an exceptional candidate to join a dynamic research team developing experimental and computational approaches to investigate the mammalian immune system. The successful candidate will play a key role in characterizing how the immune system functions so as to manipulate it in health and disease. The position will become available in Winter 2020 or later in the lab of Nicolas Chevrier (www.chevrierlab.org), and a 2-year minimum commitment is required (with possible extension).
Emphasis will be to generate new biological insights by developing new approaches to analyzing large-scale and high-throughput data (next-generation sequencing, imaging, genetic screening, etc.) generated in the lab and in collaboration with researchers and clinicians at the University of Chicago and beyond. You will work collaboratively with other data and research scientists on computational research in a fast-paced environment. Your work will be expected to enable the research of other lab members and collaborators through excellent communication, teamwork, and a focus on creating usable and accessible research software tools. You must be capable of working in an interactive team environment while conducting self-directed research within broader goals set by group.
Additionally, the Pritzker School of Molecular Engineering at the University of Chicago provides a vibrant, interdisciplinary research environment with close links to top academic and industrial institutions across the Chicago Area and provides the potential for your contributions to be used and recognized worldwide. The candidate will add to this environment and the Chevrier lab with flexibility, creativity, scientific agility, self-motivation, and strong communication skills.
• Develop, apply, document, and maintain computational tools, to support analysis by biologist colleagues without formal computational training.
• Design and evaluate computational solutions.
• Develop customized computational solutions supporting new kinds of assays and experiments.
• Understand the analytical needs of new experiments, working closely with wet-lab experimental biologists.
• Identify and resolve technical issues and propose upgrades to current software.
• Implement and optimize successful algorithms and methods to be shared for use by the broader community.
• Develop figures and reports, which 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, plan projects and experiments, and to ensure that projects support current team goals.
• Consults with other scientists or scientific literature as needed.
• Maintain and organize computational infrastructure and resources.
• Identify and resolve technical issues and propose solutions.
• Contribute to generation of protocols, publications, and intellectual property.
• Other related tasks as required.
• Excellent communication skills and the ability to interact professionally with all levels of staff and with external contacts in a fast-paced environment required.
• Excellent organization and time management skills.
• Creative, organized, motivated, team player.
Additional Job Description Section
Education, Experience, and Certifications:
• Bachelor’s in computer science or computational biology or bioinformatics or quantitative science or related field required.
• Master’s or PhD degree is a plus but not required.
• Knowledge of biology or immunology is a plus but not required. Inclination to acquire such knowledge is.
• Must possess 1 – 3 years of practical experience in data analysis, preferably in an independent project in an academic research laboratory setting during/after the completion degree.
• Background in statistics and machine learning is preferred but not required.
Technical Knowledge or Skills
• Fluency in Unix, standard bioinformatics tools (Python, R, or equivalent), and a programming language (C/C++, Java).
• Knowledge of SLURM or other job scheduler, and/or bioinformatics tools a plus.
Resume, Cover Letter, and Reference list