Cdd Post-Doc Bioinformatic

Há 5 dias

Porto, Portugal Cnrs Tempo inteiro

Organisation/Company: CNRS
Department: Institut de Recherche sur le Cancer et le Vieillissement, Nice
Research Field: Biological sciences » Biology
Researcher Profile: Recognised Researcher (R2)
Country: France
Application Deadline: 5 Dec 2024 - 23:59 (UTC)
Type of Contract: Temporary
Job Status: Full-time
Hours Per Week: 35
Offer Starting Date: 1 Jan 2025
Is the job funded through the EU Research Framework Programme? Not funded by a EU programme
Is the Job related to staff position within a Research Infrastructure? No
Offer Description The post-doctoral fellow will contribute to bioinformatic analysis of Saccharomyces genomes with a focus on studying telomeric regions using "long-read" sequencing. This includes analysis of natural and engineered strains. The post-doc will also use "machine learning" approaches to predict telomere length phenotype and its role in regulating the species fitness landscape.
Responsibilities Develop pipelines for yeast genome analysis and machine-learning based phenotypic predictions
Telomere length analysis of individual telomeres using "long-read" on a selection of newly isolated Saccharomyces strains
Analyse large scales "long-read" genomics dataset for all types of genomic variation (SNP, CNV, SV etc.)
Analyse genomic variations, GWAS and prediction of functional impact
The postdoctoral fellow will be assigned to Dr Gianni LITI's team "Population genomics and complex traits". The team is one of the founding teams of IRCAN and is located at the Faculty of Medicine of Nice. The team has all the necessary equipment for yeast genetics and genomics experiments and has access to state-of-the-art microscopy, cytometry and genomics facilities as well as computing and storage servers.
Minimum Requirements The position is open to individuals interested in genomic analyses. Prior experience in bioinformatics, machine-learning, programming and a strong background in statistical genomics is essential. The candidate is expected to develop advanced pipelines and have the ability to analyse massive scale datasets.
Knowledge Thorough knowledge of yeast genetics and genome analysis
Thorough knowledge of computer programming (R, Unix, Python, HTML)
Data collection, analysis and processing (in-depth knowledge)
Knowledge of microbiology and molecular biology
English language: B1 to B2 (Common European Framework of Reference for Languages)
Operational Skills Process large genomic data
Contribute to the maintenance of the team's bioinformatic infrastructures
Contribute to the scientific life of the team and to the close interaction with other members
Report on his/her activity to the team leader
Present data at laboratory meetings
Write scientific papers and participate in grant applications

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