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Field
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pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with colleagues from various application areas (cross-disciplinary) publication and presentation of your scientific results
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evaluate usability of system architectures such as Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference - implementation of your machine learning pipeline in Python (using e.g
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sample collections Conduct and supervision of laboratory analyses, in particular immunological assays Data management and programming in R and Python Writing and contribution to original publications
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explore concepts form several topical fields such as: - Acoustics and interfacial fluid mechanics - Advanced wavefront control in complex environments - Experimental instrumentation (Python
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automation, data science, python. The ability to collaborate in a multidisciplinary research environment is essential. Personal initiative, ability to work systematically, reliability, responsibility, teamwork
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interdisciplinary team with clinicians and engineers; You have strong programming skills in Python; You have knowledge of medical image processing, and machine learning and deep learning techniques; Written and
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(knowledge of energy systems is a plus). The ideal candidate for the position has skills in electrical grid modelling (OpenDSS, Pandapower, MATPOWER, etc.), programming skills (Python, Julia, Matlab), as
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or signal analysis • Programming in Python or R • Statistical modelling Applicants without prior AI experience are encouraged to apply, as structured AI/ML training will be provided. Dairy Cattle Welfare
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data (nationwide LiDAR coverage at 50 cm resolution). The candidate will perform quantitative morphometric analyses of landscapes and river networks near suspected active faults using GIS tools, Python
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modeling (60%); b) Experience in participating in research projects (20%); c) Experience in programming in Python and related languages (20%). 10. Composition of the Selection Jury: Ana Isabel Pereira José