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. 50% - The academic record of the candidate 2. 50% - Participation in international projects and experience in the following areas of research: System testing, cryptography, side-channel analysis
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and Data Science - Previous experience in Data Analysis and Integration, and in Information Visualization is a plus EVALUATION CRITERIA The selection will be based on the following criteria: 70% - CV 30
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developing statistical and machine learning approaches for the integration of cancer multi-omics data and the analysis of CRISPR-based screens. Responsibilities include designing bioinformatics workflows
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given to successful candidates with suitable scientific and professional curriculum such as - experience in scientific programming and in biological signal analysis, substantiated by publications and
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factors: Experience with program analysis tools. Strong programming skills required in JavaScript and Python. Proficiency in English. EVALUATION CRITERIA The evaluation takes into account the candidate's
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factors: Thorough understanding of the JavaScript. Experience with JavaScript analysis tools. Strong programming skills required in JavaScript and Python. Proficiency in English. EVALUATION CRITERIA
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to work individually and as a team. Preferential factors: Experience with program analysis tools. Strong programming skills required in Rust and Python. Proficiency in English. EVALUATION CRITERIA
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, ranking the candidates according to their classification consisting of the sum of the partial classifications assigned in each evaluation criterion, and considering the weighting factor given to each
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evaluation criterion, and considering the weighting factor given to each parameter. In this process abstentions are not allowed. In the event of a tie among candidates with the same highest evaluation score
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on the sum of the partial classifications assigned in each evaluation criterion, and considering the weighting factor given to each parameter. In this process abstentions are not allowed. In the event of a tie