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Job Information

Harvard University Postdoctoral Fellow in Machine Learning and Design of Biological Systems in Cambridge, Massachusetts

Details

Title Postdoctoral Fellow in Machine Learning and Design of Biological Systems

School Faculty of Arts and Sciences

Department/Area Science Division

Position Description

A postdoctoral position is currently available in the laboratory of Dr. Mor Nitzan at Harvard University’s Faculty of Arts and Sciences to study spatial and temporal aspects of interaction patterns in biological systems. We are looking for exceptional candidates with background in machine learning and/or computational biology.

Research will focus on both top-down and bottom-up mapping of local interactions between relatively simple dynamic entities and their emergent complex behavior. We study these questions in various theoretical and biological settings, such as cellular interactions in tissues using single cell sequencing data.

The initial appointment period is funded for one year.

Basic Qualifications

Candidates should have a PhD in computer science, physics, bioinformatics or a related field, and an interest in biology.

Additional Qualifications

Previous research experience related to biology is an advantage but not required.

Special Instructions

To apply, please send a CV, a statement of research experience and interests (two pages maximum), and the names and contact for three references to mornitzan@fas.harvard.edu.

Contact Information

Dr. Mor Nitzan

Arzy Nitzan Lab

Northwest Building,

52 Oxford St., #365.30 Cambridge,

MA 02138

USA

Contact Email mornitzan@fas.harvard.edu

Equal Opportunity Employer

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

Minimum Number of References Required

Maximum Number of References Allowed

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