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have a PhD in computational modeling/oncology, systems biology, applied mathematics, nuclear medicine physics, or a related field. Prior experience in at least one of the following is a requirement
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. The successful applicant will train directly under the supervision of Dr. David Granville, PhD, and will have an opportunity to develop their leadership skills in the laboratory by participating in overseeing
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biology for a two-year term with possibility of extension. The successful applicant will train directly under the supervision of Dr. David Granville, PhD, and will have an opportunity to develop
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set the research direction and computational approach to the data. Qualifications: - PhD in Biology, Bioinformatics, Computer Science, Statistics or a related quantitative field. - Experience working
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at research hospitals (eg. Study nurse, data collectors), and students. QUALIFICATIONS • PhD in a relevant field • Demonstrated ability to thrive in a collaborative team environment • High personal
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international scientists, clinicians, and public health researchers to make meaningful impacts to cancer detection, diagnosis, and treatment. Qualifications and Experience PhD in Bioinformatics, Computational
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Qualifications PhD in public health or related field obtained within the last five years. Proven ability to thrive in a collaborative, mixed-methods research environment. Strong personal motivation, self
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Vision conferences, CVPR, ICCV, ECCV and peer reviewed journals. Minimum Qualifications: PhD in Computer Science or a related field obtained within the last five years. Strong skills in machine learning
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: A PhD in forest operations, silviculture, forest management or a related field. Strong experience in forest operations, management or silviculture research. A background in quantitative analysis
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of data, creating diverse training opportunities. Interested applicants should have a PhD in biology, molecular biology, biomedical engineering, biotechnology, materials science, computer