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The Leibniz-Institut für Analytische Wissenschaften - ISAS - e. V. develops efficient analytical methods for health research. Thus, it contributes to the improvement of the prevention, early
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breakage models, e.g. with stochastic tessellations Development and implementation of estimation methods for the model parameters, e.g. with machine learning or statistical methods Lab work and collection
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, you need to develop and apply methods that enable the recognition of phenological stages of allergenic plants on images. Then, the phenological development of these species shall be modelled based
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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science. A wide range of quantum theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to
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theoretical methods shall be employed. A solid background in quantum mechanics and programming skills are prerequisite for this position, as is the readiness to learn and to apply new methods. For an initial
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• Highly motivated to carry out precision experiments and implement novel measurement methods • Strong initiative, effective working style • High level of creativity and drive to experiment intensely
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artificial intelligence methods. PhD Position – Hydrogen corrosion assessment combining experimental and AI approaches Reference code: 50141225_2 – 2025/MO 2 Commencement date: as soon as possible Work
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. We would therefore strongly encourage qualified women to apply for the position. Your tasks develop surrogate models to approximate high-fidelity phase field simulations, incorporating physics-informed
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methods) ▪ You a keen interest in exploring the control and readout of superconducting qubits and like to push the software interface further to enable high-quality quantum operations. ▪ You work in an