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or related fields. Experience in research or relevant activities in the project area, such as data analysis, statistical modelling, or software development. Good knowledge of statistical programming
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of indicators for water quality and quantity. The following tasks will be carried out: a) deepen existing knowledge about spectral data capable of differentiating and remotely detecting lentic habitats and the
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; b) preferential factors: Preference will be given to candidates who demonstrate strong knowledge and/or experience in the culture, functional characterization, biochemistry, and molecular biology of
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, with a weighting of 50%; Course Scientific Area, with a weighting of 50% Personal curriculum (considering professional and scientific background), with a weighting of 40%;Relevant knowledge in Nanofluids
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to assess the following sub-criteria: B - Interview – INT (30%) B.1 – Interpersonal skills (20%) B.2 – Knowledge demonstrated in the field of the call (30%) B.3 – Motivation (30%) B.4 – Language skills (20
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for contractualization, proof of academic qualifications completed at the deadline for applications, including those resulting from academic degree recognition processes. Preferential Requirements: Knowledge in thermal
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-throughput sequencing data; c) Knowledge of the Linux operating system and of computer programming languages, including Python. Workplan and objectives to be achieved: a) Management, archiving, and analysis
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(excellent) values: Applicant Merit (AM) (100%): A.1: (30%) Academic background of the candidate (including performance in related courses and previous experience in research projects). A.2: (40%) Knowledge
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Engineering, or Materials Engineering, or related areas, with knowledge in sputtering deposition of thin films and respective characterization; Masters enrolled in non-conferring courses: not having benefited