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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | 3 months ago
or application of deep neural network models; b) Mass spectrometry data analysis – 20% Practical experience, methodological knowledge and/or academic training in the analysis and interpretation of mass
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points c) Research Experience in the project area, namely in DNA extraction, target gene quantification, metagenome analysis using computational tools and statistical data processing – up to 8 points; in
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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 3 months ago
of radioligands and assistance with further preclinical in vitro and in vivo experiments # Analysis of experimental data and communication of results in work reports and internal presentations, at international
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proficiency;* 5.º - Strong sense of responsibility, autonomy in task organisation, and ability to work collaboratively; 6.º - Experience in data collection and basic data analysis, as well as an interest in
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pre-processing, including background correction and normalization.; • Develop algorithms for spectral feature extraction and chemical map generation from LIBS data.; • Apply multivariate analysis and
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or related field;* Solid knowledge in machine vision and deep learning (e.g., TensorFlow, PyTorch, OpenCV); Experience in Python programming (focus on libraries for data analysis and AI); Previous
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qualitative methodologies in the process of database management and statistical data analysis; Publications in peer-reviewed international journals and presentations at conferences in the scientific area of
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of renewable biological resources, including in relation to environmental variability. This includes the development and use of data analysis methods and models capable of describing and integrating physical and
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methodologies to the problem under study; 6 – Data analysis according to the best methodology identified; 7 – Report on activities carried out Workplace: The work will be carried out at the Departamento de
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, recording of operational context, and ensuring the quality of collected data; c) Organization, annotation, and initial pre-processing of collected data, ensuring proper structuring for subsequent analysis; d