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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 1 month ago
networks or similar machine learning technologies applied to DNA; Preferential: Experience with transcription factor motif discovery; Proficiency in high-throughput sequence alignment methods; Candidates who
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communities. This task includes soil DNA extraction, preparation of libraries for sequencing of 16S rRNA (bacteria) and ITS (fungi) barcodes, as well as bioinformatic processing and analysis of sequences
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qualifications and/or diplomas, if applicable. Enrollment in a non-degree course developed in association or cooperation between a High Education Institution and one or multiple research units. Work plan
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, microbial community analysis of anode and cathode biofilm(s) based on 16S rRNA gene sequencing and cultivation approaches for isolation and characterization of electrogenerative microorganisms. Using
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evaluated based on the information described in the detailed Curriculum vitae and other documents presented in the application. The Curriculum vitae must be structured to reflect the sequence of the criteria
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of appropriate genetic markers, and preparation of samples for high-throughput sequencing; c) Management, pre-processing and analysis of high-throughput sequencing data obtained through DNA metabarcoding
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of contractualization. Possess advanced knowledge and competencies in the field of health sciences, such as neurology and/or neurobiology, aligned with Level 7 of the European Qualifications Framework (EQF). Meet at
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of polychaetes and extraction of DNA/RNA. iii) Analysis of sequences and expression of genes of interest. iv) Determination of the physiological and pathological condition of the target organisms. The remaining
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the motivation letter; Knowledge in PCR and library preparation for Illumina sequencing- information provided in the CV and/or in the motivation letter; Proven scientific experience in the above-mentioned topics
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Biology or overall large-scale sequencing data analyses; b. Proficient in R and Python scripting; c. Experience in analysis of transcriptomic data (RNAseq) enclosing large sample size; d. Experience in