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respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in building science, architecture, mechanical engineering, construction, or closely related
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, or AI inference combined with traditional FPGA development workflows. Familiarity with AMD Versal SoC architecture and the Vivado/Vitis tool chains. Basic understanding of x-ray or neutron scattering is
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machine learning algorithms on HPC architectures Special Requirements: Applicants cannot have received their Ph.D. more than five years prior to the date of application and must complete all degree
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. Understanding of machine learning algorithms (gradient descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). A broad understanding of machine learning methodologies and
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, or AI inference combined with traditional FPGA development workflows. Familiarity with AMD Versal SoC architecture and the Vivado/Vitis tool chains. Basic understanding of x-ray or neutron scattering is
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, and measure success. Basic Qualifications: PhD degree in a related scientific field (e.g. architecture, architectural/mechanical/electrical engineering) completed within the last five years. Proven
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software for the simulation of electrochemical systems for applications such as material synthesis, electrochemical reduction and separation processes. Participate in the design and architecture