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machine learning algorithms to support the traceability of the beef’s geographical origin. She/he will participate in all stages of the project, including planning and supervision of sample collection and
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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. Possible research topics include, but are not limited to, physical variability and its influence on plankton distribution; ecological connectivity and larval dispersal; the transport of organisms and
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using advanced seismological and geophysical methods, including surface-wave tomography, receiver functions, reflected seismic phases, joint inversion, and Distributed Acoustic Sensing. The main objective
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, generalized transverse-momentum-dependent distributions (GTMDs), and electromagnetic and gravitational form factors, using continuum dynamical methods. Mandatory requirements: Ph.D. in Nuclear Physics, Hadron