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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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Tecnologia. OBJECTIVES | FUNCTIONS Perform bioinformatics analysis of coffee multiomic data, organize and curate the project's datasets for publication in accordance with the FAIR principles. BINDING
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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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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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learning methods to digital pathology Development of deep learning algorithms for the computational analysis of whole-slide images. The objective is to identify relevant biological features and to perform