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statistical physics, applied probability, and population genetics; develop inference frameworks that link model predictions to genomic and epidemiological data; design controlled computational experiments
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contexts (predicting the desired effect in humans vs. ruling out safety risks); transferability of approaches and models from research into the application of NAMs in the safety assessment of chemical
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underexplored. Rather than functioning as neutral tools, algorithmic models translate complex realities into scores, rankings, classifications, and predictions. In doing so, they shape how problems are defined
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: 10 May 2026 Apply now Predicting ecosystem dynamics under global change requires accurate, high-resolution soil information. Existing global soil maps are largely based on empirical machine learning
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, support decision-makers, and advance debris-flow modelling for future research. In this PhD, you will carry out field measurements and run numerical simulations to better understand and predict debris-flow