86 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"Iscte-IUL" positions at Harvard University
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project areas: Building and integrating software Community building and outreach Usability and UX Writing math proofs Machine learning and differential privacy Privacy, ethics, policy, and responsible use
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of at least some of the following: – Extensive independent research experience – Creativity and independence – Experience analyzing hyperspectral data and developing machine learning models - Genetic
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protocols, which involves conducting literature reviews and eliciting required data elements Understanding of and experience with quantitative methods (simulation modeling, optimization, and machine learning
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date to be determined. Basic Qualifications A PhD related to programming languages by the start date. Experience in machine learning and formal verification. Individuals with a demonstrated track record
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Bioinformatics / big data , Biological Data , data science , Interdisciplinary Cellular and Molecular Biology / Cellular and Molecular Biology , RNA Biology Computer Engineering / Cloud Computing
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. Cross-Disciplinary Fellowships (CDF) are for applicants with a Ph.D. from outside the life sciences (e.g. in physics, chemistry, mathematics, engineering or computer sciences), who have not worked in
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date to be determined. Basic Qualifications A PhD related to programming languages by the start date. Experience in machine learning and formal verification. Individuals with a demonstrated track record
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organization skills Interest in learning and strengthening existing skillsets Strong technical and programming skills, familiarity with current deep learning techniques, with a focus on computer vision Special
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for opportunities abroad. These grants present an excellent opportunity for recently minted scholars to deepen their expertise, to acquire new skills, to work with additional resources, and to make connections with
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training activities focused on biomedical research methods in healthcare. Under the close supervision and mentorship of Dr. Zitnik, the Associate will: 1) Explore and learn about state-of-the-art techniques