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Collaborate in the use of remote sensing and machine learning methods to detect A. longifolia and to monitor the spread and effects of the biological control agent (occasional collaboration). Activity 4
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for developing machine learning models for the automatic identification of species from images collected through electronic monitoring systems (Work Package 3 – Bycatch Monitoring). The candidate will be involved
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, and eye tracker data. Work Plan: - Multimodal feature extraction from EEG, HRV, gaze dynamics, and pupil size data; - Signal fusion and model training using interpretable machine learning models (e.g
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that combine machine learning and classical methods. Work Plan: -State-of art revier and publication of a review paper -Development of classical approaches -Development of hybrid approaches -Journal publication
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for the analysis of complex experimental data; • Development and implementation of strategies for multiomics data integration and systems biology; • Use of Python and R for statistical analysis, machine learning