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. Scientific Area(s): Bioinformatics, Computational Biology or Microbial Evolution Work Plan and Objectives: The post-doctoral fellow will work closely with experimentalists in Isabel Gordo’s lab to study
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in: bioinformatics; routine molecular biology techniques (DNA extraction, PCR, electrophoresis); beekeeping and monitoring of bee colonies. 3. Work Plan: 1) Management, monitoring, sampling, and
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support from Fundação para a Ciência e a Tecnologia, IP.P. / MCTES through national funds (PIDDAC), 2023.17326.ICDT. Scientific Area(s): Bioinformatics, Biology, or related areas Work Plan and Objectives
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against atropine and scopolamine using a SELEX methodology; Bioinformatics analysis and characterization of nucleic acid libraries; Development of an aptamer-based LFA biosensor for the detection
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selection of aptamers for Shiga-like toxins of E. coli and determination of their affinity; Evaluation of aptamer libraries, based on data generated by sequencing; Application of bioinformatics tools
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, Bioinformatics analysis Work Plan and Objectives: The post-doctoral fellow will work very closely with experimentalists in Waldan Kwong’s lab to study bacterial strain interactions in the gut of the honey bee
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regulatory networks in pathogenic yeasts, with impact on their pathogenesis, in order to strengthen knowledge regarding less well-studied yeast species. From the bioinformatics standpoint, the work will focus
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 5 days ago
” Workplan: In this project we aim at creating novel mathematical and bioinformatic models, based on real and validated functional data, which will define the impact of nucleotide alterations (NucAlts) in
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political refugee status are eligible to apply for this competition. Candidate admissibility requirements: Mandatory requirements: Have a Master degree in Informatics Engineering, Bioinformatics, Chemical and
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Qualifications • Master's degree in Bioinformatics, Data Science or related fields. Skills and Preferred Factors Proficiency in programming languages applied to data science (e.g., R, Python, and Bash, among