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available under the following conditions: OBJECTIVES | FUNCTIONS The selected candidate will be a member of the research project SafeIaC, which aims to create the first solution for reliable analysis and
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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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the following conditions: OBJECTIVES | FUNCTIONS POSITION 1 | Blockchain Interoperability - A Data-Driven Analysis of Interoperability Protocols and Cross-Chain Transaction Patterns Collect, structure and analyze
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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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. 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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developing statistical and machine learning approaches for the analysis of CRISPR base editing screens and their integration with large-scale genomic annotations derived from variant effect predictors
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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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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 among candidates with the same highest
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components, namely: The assessment of the curriculum vitae and other documentation presented is made in according to point 8 of this notice. This component of the evaluation is expressed in a scale of 0 to 100
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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