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reconstruction, 3D modelling software (Autodesk Revit, Dynamo), including open-source frameworks and algorithms for structural and M&E BIM reconstruction. 3. Experience in Python programming, machine learning
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in the design, implementation, and maintenance of data pipelines and leading/assisting in building algorithms for deep learning with close collaboration from the study team. While programming
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. This project employs massive-scale genome sequencing, data that will enable a wide range of novel, independent projects. The project also involves a substantial theoretical component including algorithm
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, especially the toroidal spectrometer, construction and commissioning of the MOLLER detector at Jefferson Lab ● Development of the SOLID software framework, tracking algorithms, DAQ subsystem and various
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skills Excellent scientific writing ability and good communication skills Knowledge of scientific programming language(s), computer simulation, and quantum computing algorithms All tasks and job
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-fidelity qubits operations Design and implementantion of automatic calibration techniques for fast tune-up Implementation and benchmarking of quantum algorithms About you You have a relevant PhD deegree
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Qualifications - Experience in developing algorithms for analysis of biological data. - Experience with single cell and spatial transcriptome data analysis. - Experience in supervised and unsupervised machine
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within the last 0-5 years) in computational science, mathematics, physics, or a related field with a focus on image processing. Proven experience in algorithm and software development. Expertise in Python
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encompass: Catalysts Synthesis: Utilize your expertise in materials synthesis to develop novel catalysts guided by machine learning algorithms Catalyst Performance Evaluation: Utilize aqueous electrochemical
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inverter-based resources for performing real-time simulations in Opal-RT. Develop and prototype advanced control algorithms for grid forming and grid following inverters. Develop and demonstrate