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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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team setting; Training of other HQP Qualifications Candidates must hold a PhD obtained within the last 5 year, or MD obtained within the last 10 years. Applicants should have a strong research background
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partners. Minimum Qualifications A PhD in Forestry, Environmental Science, Ecology, or related fields. Strong expertise in forest carbon accounting, including carbon stock quantification. Proven experience
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Qualifications A PhD in Forestry, Environmental Science, Ecology, or related fields. Strong expertise in forest carbon accounting, including carbon stock quantification. Proven experience in biodiversity
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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
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are available immediately and intended for early-career scientists with an advanced degree (PhD). The selected fellow(s) will join the research group of a Principal Investigator through a TQT-funded project, and
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research teams to drive impactful studies Mentor trainees in different aspects of clinical research Minimum Qualifications PhD in public health or related field obtained within the last five years. Proven
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the laboratory Assist in the management of laboratory resources and maintenance of research protocols Qualifications/Requirements of Position Qualifications: PhD in Biological Sciences or a related field, with 0-5
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individuals immersed in any academic discipline. Eligibility Fellows will normally have a PhD and a record of scholarly research in an area related to the CSRS mandate. Typical applicants may be retired faculty