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goals Teach and co-supervise BSc and MSc student projects Participate in Arctic field campaigns We expect you to have: Experience in working with large data sets and development of algorithms. At least
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across the value chain. Using Bayesian Optimization / Modern Design of Experiment, we build the data-foundation to enable true hybrid development between humans and advanced learning algorithms such as
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have the opportunity to engage in pioneering research, collaborate with a dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies
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Job Description Are you excited about developing advanced models and algorithms to better understand and predict human decision-making? Are you interested in integrating behavioural models with
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have the opportunity to engage in pioneering research, collaborate with a dynamic and multidisciplinary team, and advance the field of quantum computing through innovative algorithms and technologies
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nonlinear fiber-optic channel. The project will cover both algorithm development as well as experimental implementations. We offer an opportunity to develop expertise in various domains, including but not
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quantitative metrics of faults and defects, integrating statistical metrics into active inspection behaviors. Collaborate with a multidisciplinary team—from the AUTOASSESS project—to integrate your algorithms
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detector model for radiation sensor readout. Training and optimizing ANN-based signal processing algorithms. Working with synthetic data to enhance electron tracking performance. Collaborating with the i
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binding oracles. Develop an algorithm to bias the generative models towards desirable properties, such as expression and developability. Develop and validate optimization tools for performing (Bayesian
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algorithms, are becoming increasingly flexible and capable of operating in complex and dynamic environments. To maximize their potential, these robotic functions must be effectively contextualized within