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database design and maintenance Experience in interpreting raw data streams from radio telescopes or similar data Experience in high performance computing, especiallyinvolving massively parallel applications
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the main point of contact with the LIS vendor for system support and maintenance. Other laboratory computer applications may be included in the scope of work as the position evolves. Key Responsibilities
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environments Experience with parallel computing environments, HPC in a Linux environment Experience with surrogate modeling Experience with data analytics techniques Familiarity with C++ and GPU programming
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environments Experience with parallel computing environments, HPC in a Linux environment Experience with surrogate modeling Experience with data analytics techniques Familiarity with C++ and GPU programming
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-edge techniques with clinical sample analysis, develop novel animal models to conduct mechanistic studies with parallel patient sample analysis, and test preclinical innovative immunotherapy strategies
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-performance computing. SLU provides access to extensive datasets that can be used to develop machine learning methods and automated analyses relevant to the position. Long-term datasets are available from, i.a
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destination. Job Summary The Data Science Institute (DSI) Tech staff is responsible for the design, operation, and security of all computing infrastructure within the Data Science Institute, including research
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properties. In parallel, they continuously sense and respond to diverse mechanical cues from their environment, including adhesion, stiffness, tension, shear, pressure, and confinement. These cues
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tools such as scientific computing, High Performance Computing (HPC), Big Data (Spark, DBMS), Machine Learning, cloud computing services (AWS, Azure, GCP), Massive Parallelism paradigms (MPI, OpenACC
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 22 days ago
architecture, health informatics, data privacy Computational Science: scientific computing, high-performance computing, large-scale parallel systems, modelling and simulation, bioinformatics, computational