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algorithms and running these models on high performance GPU computing clusters. The training will also provide knowledge about the recent advances in large language models. Mentoring: The
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, microfluidics, laboratory automation, and GPU computing infrastructure. The opportunity to develop AI methods and scientific software that are directly deployed on cutting-edge experimental
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and to build devices based on quantum phenomena. Experts in this new discipline of quantum technologies are applying their discoveries in computing, communications, and sensing. CQT is hosted by the
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excellent infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing
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infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure
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systems, including embedded and resource constrained systems with various heterogenous computing topologies Additional responsibilities include Assisting with development of GUI software tools to
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courses at the department each year. You can find more information about us on the Department of Information Technology website. The position is hosted by the Division of Scientific Computing (TDB
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Python and modern deep learning frameworks. ● Experience with High-performance Computing Infrastructure and GPU clusters. ● Strong research background in multimodal modeling, representation learning
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principles and research data management. Experience with high-performance computing, cloud computing, GPU acceleration, or distributed data processing. Experience participating in international scientific
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CNS tumour cohorts and continuously growing multimodal datasets with linked molecular and outcome data State-of-the-art research infrastructure including digital pathology, dedicated GPU computing