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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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. Depending on background and interests, the role may involve analysis of high-throughput epigenomic and genomic data from tissue and liquid biopsy samples; development of scalable, reproducible workflows using
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Familiarity with omics approaches such as scRNA-seq, proteomics Programming or data analysis skills such as R, Python, or similar Experience in international collaborative projects Experience with laboratory
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central experimental role in the project and work closely with a dedicated postdoc supporting advanced computational analysis and interpretation of data. The position offers substantial scientific
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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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but also in a team you hold a PhD in life sciences (e.g. molecular biology, biochemistry, genomics, computational biology or related areas) you have experience in NGS-based assays and NGS data analysis
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appropriate analysis strategies for genetic and ‘omic data integrated into epidemiological investigations; Collaborating with external (including many international) researchers to lead or contribute to large
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histology or imaging techniques. ⦁ Familiarity with R or other statistical tools for data analysis. The postdoctoral researcher and PhD-student positions are initially limited to 2 and 4 years
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of mathematics, e.g. participation to public events open to high-school students, or to the general public Your profile PhD of high quality in mathematics, with focus on stochastic analysis and related areas
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(TBI). The research will use in vitro techniques and in vivo mouse surgery models. A solid wet bench experience is required. Qualifications: 1). Recent PhD or equivalent degree in neuroscience, molecular