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Field
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operation · Application of artificial intelligence or machine learning in energy or engineering systems 5. Strong programming and modelling skills using relevant tools such as Python, MATLAB
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by August 2025. 1. Please upload verification as an additional document in the document upload section. 2. Earned PhD in nursing or health-related field and a strong work ethic and commitment
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at NYU Abu Dhabi, candidates are expected to have a strong interest in experimental research and collaborate with applied mathematicians closely. PhD holders with a solid publication record and aims
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Institute faculty, in areas such as: * Machine Learning and Computer Vision * Natural Language Processing and Data Science * Biomedical Informatics and Computational Neuroscience * Mathematical/Theoretical
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Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) PhD (or foreign equivalent) in Physics, Electrical Engineering, Material Science or closely related field in hand
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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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preferred. Proficiency in computational tools such as MATLAB, Python, R, or machine learning applications in immunology is desired. Candidates should have a PhD in Chemistry, Chemical Engineering
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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, challenging project. Learning on the job isn't just a benefit – it's a must. Education, Qualifications and Experience Essential Criteria Applicants should hold a PhD in a relevant area of Engineering
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, excellent communication skills, excellent computer literacy. Certifications/Licenses Required Knowledge, Skills, and Abilities PhD in life sciences. Experience with proteomics, bioinformatics, mass