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Field
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. The candidate will contribute to the development of empirically validated methods for identifying and mitigating such effects. The research will involve experimental studies, neurophysiological methods (e.g., eye
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Short overview of PhD opportunity The PhD studentship aims at studying and developing more comprehensive user interfaces for computer-aided decision-making processes, which can benefit from 3D/360
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/ physics/ meteorology/ engineering/ biology. Experience in a computer programming language (e.g. Fortran, Python). A general understanding of the importance of the scientific method is essential. A previous
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, geomagnetism) and the development of corresponding numerical methods. We offer the opportunity to work in a small interdisciplinary research group consisting of mathematicians, computer (geo)scientists, and
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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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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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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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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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, personalised interventions in cancer, and interdisciplinary collaboration? If you possess strong competencies in health economics research methods, you might be the ideal candidate for our PhD position. Research
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infectious disease epidemiology and mathematical modelling in Biology and Medicine. Experience in parameter estimation, knowledge of Bayesian methods and computer programming skills would be an advantage. Good