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genomic data. Responsibilities: Primary responsibilities encompass: Supervising graduate students and postdocs in Big Data Biology, including Data Structures and Algorithms, Machine Learning (ML), and
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Assist Prof in Next-Generation Approaches of Remote Sensing for Applications to digital soil mapping
spectroscopy for multi-scale soil fertility mapping and assessment, Develop hybrid approaches combining radiative transfer model and Next-Generation Approaches of Remote Sensing such as machine learning (ML
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Assist. Prof in Next-Generation Approaches of Remote Sensing for Applications to Digital Agriculture
crop growth and yield, Develop hybrid approaches combining radiative transfer model and Next-Generation Approaches of Remote Sensing such as machine learning (ML) regression algorithms for timely and
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and Research: The professor will develop research activities in several aspects of computer science, including but not limited to algorithms, databases, cloud computing, machine learning, operating
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photonic processors, superconducting qubits, and quantum-inspired machine learning for groundbreaking computational capabilities. Proposal Budget: The proposal budget limit is R$5 million (roughly 1 million
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at the scientist/professor level depending on the CV and past experience of the successful candidate. The candidate is expected to combine machine learning and geosciences to develop innovative research related
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into the cancer genome and epigenome using long-read sequencing and machine learning Gaining novel insights into the cancer genome and epigenome. This project will generate and analyse nanopore long-read sequencing
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Climate Science, Hydrology, Environmental Science, or a related field. Experience in machine learning or AI applications in hydro-climate studies. Strong background with GIS tools and spatial analysis
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machine learning, and who is willing to take on the challenges of research and development of foundation models for the TRIP-AGIS project and the BDR from the perspective of their application to life
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interdisciplinary position requires combined expertise in a variety of fields including biostatistics, machine learning, and transcriptomics data analysis. The successful candidate with high-quality interpersonal