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appropriate balance of synergy and complementarity with materials science and engineering research already underway. Alignment with Materials Ageing, Performance, and Lifetime Prediction and a willingness to
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. Deep expertise in predictive modeling, classical ML algorithms (e.g., decision trees, gradient boosting), large language models (LLMs), generative AI, MLOps, and AutoML using frameworks like PyTorch
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-based transfer learning classification model for two-class motor imagery brain-computer interface. International Journal of Neural Systems (IJNS). https://doi.org/10.1142/S0129065719500254 * Kudithipudi
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/trait data) Conducting statistical modeling, feature selection, and predictive analytics for forest health, resilience, and biomass estimation Supporting data preprocessing, cleaning, normalization, and
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diversity expected under different conditions of resource competition. The post-doctoral fellow will develop new modeling frameworks, using R or a related language. Where to apply E-mail positions@gimm.pt
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supervisor(s). The report models, performance evaluation criteria, and the grant contract model are those approved under the University of Coimbra's Research Grant Regulations. Where to apply Website https
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analytical approaches and technological tools (e.g., artificial intelligence, remote sensing, environmental informatics, predictive modeling, and/or environmental genomics). Research should address pressing
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workflows that integrate modern AI and machine learning concepts (e.g., surrogate models, adaptive sampling strategies) into the drug discovery pipeline to increase throughput and predictive accuracy
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‑learning techniques in an applied or production‑like environment, including classification or predictive modelling. Experience working with Python and common data‑science libraries (e.g. pandas, scikit‑learn
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clinical study to develop prediction models for periodontal disease progression (funded by the National Institute of Dental and Craniofacial Research). Primary responsibilities of the Study Coordinator will