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of Physical Medicine & Rehabilitation to work with Dr. Emily Briceno. Primary Project (NIH/NIA RF1AG088009): Mild Cognitive Impairment and Alzheimer's Disease and Related Dementias: Cross-national longitudinal
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knowledge graphs to develop and test new measures of innovative potential. The project will also assess how these measures relate to multiple indicators of research impact in biomedical research, with a
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communication skills. The position calls for robust knowledge and hands-on experience in cell and molecular biology, and an aptitude in computational tasks. Familiarity with advanced techniques such as single-cell and
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resilience to water-related challenges in transboundary regions, emphasizing interdisciplinary research and especially the integration of Traditional Ecological Knowledge with classical western science through
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preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future. Responsibilities
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and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future. Responsibilities* Fellowships are renewable for up to a
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organizational needs, performance evaluations, and secured funding. The salary range for this position is $60,000 - 70,000. Factors used to determine salary include experience, knowledge and skills
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of demonstrated technical knowledge of machine learning techniques Proficiency using data science tools (e.g., Python, R, MATLAB, Jupyter Notebooks) Excellent verbal and written communication skills including
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collaborative team Write manuscripts for publication Present research at internal and external meetings Required Qualifications* PhD in Cognitive Science or a related field Ability to work with complex clinical
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), Long Short-Term Memory Networks (LSTMs), State-Space Models, Diffusion Models, Transformers, and/or Graph Neural Networks (GNNs). Knowledge of Physically-Informed or Physically-Aware AI/DL Architectures