【简介】博士后招聘网整理分享“美国阿尔贡国家实验室2019年招聘博士后职位（计算与系统生物学）”，浏览查询更多博士后招聘计划请访问博士后招聘网。

美国阿尔贡国家实验室计算与系统生物学博士后职位招聘

Postdoctoral Appointee-Computational and Systems Biology

· Argonne National Laboratory

· Location: Lemont, IL

· Job Number: 7059197 (Ref #: 406878)

· Posting Date: Aug 7, 2019

· Application Deadline: Open Until Filled

Job Description

Position DescriptionConducts basic research in computational and systems biology to understand safeguard mechanisms within bacterial systems. Develops novel machine learning algorithms for predicting activity of Cas9-gRNA complexes as a function of gRNA sequence within bacterial systems under diverse physiological conditions. Development of Machine Learning approaches to be used to iteratively design, validate and improve experiments that will result in robust safeguard systems for these bacterial systems.

Position Requirements

· Doctorate Degree in a related field or discipline.

· Knowledge in computational biology, with emphasis on systems biology and regulatory network modeling

· Knowledge in modeling complex biological systems,

· Interdisciplinary research involving computational biologists, computer scientists, and experimental biologists

· Machine learning, statistical modeling, and quantitative techniques for genomics,

· Development, validation and deployment of deep learning approaches using Tensorflow/ Pytorch,

· Working knowledge of building deep representations of genomic data, and

knowledge of Python and other relevant programming languages (C/C++, Julia).

· Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork.

Argonne is an equal opportunity employer, and we value diversity in our workforce. As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne prohibits discrimination or harassment based on an individual's age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.

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