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sciences Strong background in deep learning, with experience in probabilistic models (e.g., Variational Autoencoders, Bayesian approaches) Proficient Python programming for machine learning and scientific
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and engineering optical setups Experience with coherent control of quantum systems Competence in electronics design and hardware control Ability to acquire and process large datasets Enthusiasm
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and maintenance of monitoring buoys and related sensor systems. Apply image analysis and machine learning techniques to ecological datasets. Develop and implement multi-platform monitoring frameworks
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are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication
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for application. As a successful candidate you are expected to: shine in individual and collaborative research, either to assist groups of bachelor’s students in doing homework or co-teach advanced courses relevant
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hardware realization of neuromorphic systems, bridging neuroscience and electronics. The project combines expertise in circuit design, machine learning, and neurotechnology, and aims to deliver innovative
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sluice, which will then be used in a learning framework to design an automatic controller to optimize the usage of the sluice under various conditions. The other project will address challenges related
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who teach up to 20% of their working hours, to participate in the Teaching and Learning in Higher Education program (without hourly compensation). Qualification requirements The successful applicant
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of excellent research, innovative solutions, education or learning, we must make a positive difference to society and contribute to a sustainable future. We do this by cultivating talents and creating the best
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solutions, education or learning, we must make a positive difference to society and contribute to a sustainable future. We do this by cultivating talents and creating the best environments for research and