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. Describe a deep learning project you have executed—ideally a creative use of a vision transformer, U-Net architecture, or Diffusion model that you trained yourself. Projects in computer vision for microscopy
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slowdown at the glass transition, remains a major computational challenge. This Doctoral student project addresses this by combining generative AI models and machine-learned interatomic potentials
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for biotechnology. By combining mecha-nistic, statistical, and machine-learning models with automated experimental execution, the project will enable traceable, reproducible, and metadata-rich experimental planning
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science, artificial intelligence, computer vision, mobile robotics, machine learning, data science and analytics, or be able to demonstrate an equivalent professional practice and engagement. Previous experience in
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About the Opportunity About the Institute Do you want to be part of an exciting new Institute focused on combining human and machine intelligence into working AI solutions? We are launching a
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sources, both on-premises or in the cloud. Ensures the seamless and secure transfer of data, optimizing for performance, integration and reliability to enable subsequent data transformation and modeling
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of department computing assets, including process of requisitions. A successful candidate will be self-motivated, interested in learning and troubleshooting; a team player, hands on and creative; and have the
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an annual budget of 17 MCHF and about 170 researchers and collaborators, Idiap is today a key Swiss research institute in multiple AI fields, including machine learning (including deep learning, foundation
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modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. The position is in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department
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Ability to lead and work in teams Essential Application/Interview Experience and capability in blast computational simulations using codes such as Viper:: Blast, machine learning, and/or LS Dyna Desirable