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of the) [map ] Subject Area: Mathematical Machine Learning Appl Deadline: 2025/10/13 11:59PM (posted 2025/09/16, listed until 2025/10/13) Position Description: Apply Position Description Join Us! Are you
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consortium, 23 partners across Europe, aims to unlock the hidden potential of global metagenomic sequence space using a combination of synthetic biology, machine learning (ML), and ultrahigh-throughput
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proactively. Experience in design, prototyping, basic programming, AI and/or machine learning are a plus. International PhD candidates with scholarships below the applicable IND income standard (currently
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GNSS, wireless navigation and machine learning is desirable Additional skills that are highly appreciated in this position are the willingness to work hard and to learn more about the fascinating
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on the application of machine learning in satellite communications (20 points). Participation in European Space Agency projects (20 points). Other skills that are valuable, but not mandatory are: Knowledge of over
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-connectivity Communication system modelling, performance analysis, and simulation. Optimization tools and machine learning techniques. Hands-on experience with software-defined radios (SDRs) and/or
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synthetic biology, machine learning (ML), and ultrahigh-throughput screening (microfluidics) to discover new enzymes and bioactive molecules with applications in biotechnology, medicine, and sustainability
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: MSc in materials science engineering. Backgrounds in chemistry, physics, computer science or a related area are also welcome. Good expertise or strong interest in numerical modeling, machine learning
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machine learning methods to investigate how ecosystem water stress and drought disturbances affect relevant forest ecosystem functioning at various scales. It will enable advanced assessment of forest
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to optimization problems with possible topics covering: Variational quantum algorithms for optimization Quantum annealing Quantum inspired optimization Quantum machine learning with a special emphasis on classical