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Field
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— The score obtained in the curricular evaluation method is expressed in numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury deliberates by vote justified according
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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Responsibilities: Build and analyze dynamical system models (multiscale, QSP, PBPK, PK-PD). Apply numerical methods, optimization, and parameter estimation to calibrate models to experimental/clinical data. Perform
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Machinery Design. Other requirements to consider Teamwork. Specific Requirements Educational Requirements: Fluid Mechanics. Advanced Mechanical Engineering (or similar). Numerical Methods in Fluid Systems and
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, in Portugal or abroad. 6.2 — The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury
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the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering the valuation up to two decimal places. 6.3 — The jury deliberates by vote justified according to the criteria of evaluation
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Development of robust design methods Uncertainty quantification and management in structural design Processing optimisation and thermal analysis of polymers Non-destructive testing Experimental characterisation
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development techniques (numerical methods, solution algorithms, programming models, and software) at scale (large processor/node counts). Experience with use of artificial intelligence and machine learning in
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of science and technology or system of higher education, in Portugal or abroad. 6.2 — The score obtained in the curricular evaluation method is expressed on a numeric scale of 0 to 20, considering
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analytical and numerical methods for the investigation of novel quantum magnetic states of matter in frustrated spin systems. Methods to be applied include, e.g., field theory approaches, exact diagonalization