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Field
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heavy software development component. The successful candidate will perform research in the application of machine learning (ML) techniques to the finite element method (FEM) in the context of composites
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pre-processing), mining dictionary data, and developing novel algorithms for time-sensitive word sense disambiguation (WSD) in Latin, contributing to the creation of a 100-million-token annotated corpus
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to work on Bioinformatics and Computational Biology in Cancer Genomics and Immunology. This position will be involved in the development and/or application of computational approaches to understand
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environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental sustainability. You will focus on processing
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developments, algorithmic implementation, and analysis. Experience with electronic structure and dynamics, non-adiabatic molecular dynamics, and coding is strongly selected for. Please seehttps
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predictions. (2) Develop numerical algorithms and computing software, such as electrical/thermal transport-related codes, machine learning, high-throughput computing, etc. Materials should be sent to ttzhang
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calculations Expertise in one or more of the following: computational methods, software and algorithm development, high-performance computing, and data analysis Proficiency in relevant programming languages (e.g
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research subject for this position is development of distributed processing strategies and algorithms for Large Intelligent Surfaces, including both joint baseband processing and synchronization across
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the development of innovative mathematical and computational algorithms. As our new Postdoctoral Researcher, your main responsibilities will include: developing and implementing advanced mathematical and
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-series modeling, and clustering algorithms. The candidate is expected to lead an effort to prepare generalized ML techniques for data quality monitoring for tasks across multiple HEP experiments