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models for high-dimensional and functional data ”, led by Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available
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translational science, leveraging molecular, cellular, and animal model systems as well as patient-derived samples to uncover mechanisms of disease heterogeneity and progression and identify novel therapeutic
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Water consumption under various application parameters Impact of dosing changes on crop quality Economic efficiency Impact on variability of soil properties Predictions based on AI models Supervisor
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defines the basic properties and differences of VR/AR, describes their advantages and disadvantages, as well as their practical use in industry. The doctoral student will design three-dimensional models
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MORE – Laboratório Colaborativo Montanhas de Investigação – Associação | Portugal | about 9 hours ago
, modeling and simulation of industrial processes. Proficiency in chemical process simulation software (e.g., gPROMS, Aspen, DWSIM, UNISIMDESIGN). Strong programming skills in Python aConditions: The person
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modeling, and AI experts, as part of the international project M2 LInES (https://m2lines.github.io) . You can read about some of our recent work here: Dheeshjith et al. 2025 , Duncan et al. 2025 , Pedersen
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and the safety implications arising from these interacting processes. You will use and extend PyBaMM, which is an open-source Python-based battery modelling framework (https://pybamm.org
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chemistry and structural biology to understand structure and function of biological macromolecules and to manipulate their function, e.g. by drug development. More information at https://www.compchem.lu.se
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Your Job: In an interdisciplinary team, you will implement approaches for the automated, large-scale availability and integration of energy system data and models, applying data science methods