Genetically Engineered Machines Professors in Global

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George Church
Harvard-MIT Health Sciences and Technology United States of America
genetic engineering
gene targeting
synthetic biology
bioengineering
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Tom Ellis
Imperial College London United Kingdom
synthetic genomics
genome engineering
synthetic biology
engineered living materials
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Huimin Zhao
University of Illinois United States of America
genome engineering
synthetic biology
machine learning
directed evolution
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Elizabeth Bhoj
University of Pennsylvania United States of America
genetics
genome sequencing
molecular genetics
gene discovery
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Christian Jacob
University of Calgary Canada
genetic algorithms
genetic programming
evolutionary algorithms
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Krishna Kumar
Toronto Metropolitan University Canada
genetic algorithms
genetic programming
machine learning
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Anatoliy Markiv
King's College London United Kingdom
genetic engineering
synthetic biology
molecular genetics
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Peter Glazer
Yale University United States of America
gene editing
genetics
gene targeting
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Amos Storkey
University of Edinburgh United Kingdom
generative ai
generative models
machine learning
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Ran Brosh
New York University United States of America
genome engineering
genetics
synthetic biology
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Zhenya Ivakine
University of Toronto Canada
genome engineering
gene editing
modeling of genetic diseases
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Carl De Boer
University of British Columbia Canada
synthetic genomics
genetics
machine learning
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Lars Steinmetz
Stanford University United States of America
genetics
genomic technologies
synthetic biology
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Harris Wang
Columbia University United States of America
genome engineering
synthetic biology
combinatorial genome editing
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Hao-wen Dong
University of Michigan United States of America
generative ai
machine learning
human-centered ai
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Nikolai Windbichler
Imperial College London United Kingdom
genetics
gene drives
molecular genetics
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Miklós Csűrös
Université de Montréal Canada
genetic algorithm
evolutionary genomics
genome sequencing
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Paul Henderson
University of Glasgow United Kingdom
generative ai
probabilistic machine learning
machine learning
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Mi Park
University of British Columbia Canada
generative ai
statistical machine learning
theoretical machine learning
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George Church
Harvard University United States of America
genetics
genomic sequencing
synthetic biology
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Alex Taylor
King's College London United Kingdom
modified dna
synthetic genetic polymers
synthetic biology
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