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- Universitat Politècnica de Catalunya (UPC)- BarcelonaTECH
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codes is essential. Experience with modelling conjugated organic molecular-based systems (e.g. electronic structure, charge transport) would be particularly highly valued. Experience in coding with Python
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platforms. Experience in development of digital twins or physics-informed machine learning models. Experience in programming (e.g., Python or equivalent) and development of control or data acquisition
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analysis. Background in statistical or physical models of proteins (e.g., Potts models, energy landscapes, coevolution). Strong background in biophysics. Programming skills in Python, R, C++. Experience
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at CRAG (from basic science to applied research using plant experimental model systems, crops and farm animals) make extensive use of genomic technologies and large sets of genetic and genomic data (https
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statistical analysis of neuroimaging data. Implement, document, and maintain analysis scripts using Python and/or MATLAB. Integrate cognitive, affective, behavioural, and neuroimaging datasets to test
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to the publication of the call for applications: https://seu.ub.edu/ofertaPublicaCategoriaPublic/listPublicacionsAmbCategoria?categoria.id=855899 Where to apply Website http://www.ub.edu/caiac/solBeca?idConvocatoria
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coordinating scientific tasks or contributing to collaborative research projects. Experience with data processing and statistical analyses in R or Python is an asset. Experience with emerging contaminants
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computing, control theory, computer vision, or numerical simulations. Experience with Python-based scientific programming Excellent problem-solving skills, Ability to work collaboratively in a
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the following software: Stata, R, Python, Matlab. Excellent command of written and spoken English, with the ability to draft academic papers, research reports and/or policy briefs in English. Evidence
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complementary energy ranges. Tasks and Responsibilities The successful candidate will: Participate in the commissioning of the array of Large-Sized Telescopes (LSTs) of the CTAO-N observatory (https