Data Science Lead

hace 2 semanas


Valencia, España Sebibc A tiempo completo

.IPREMOM is a FemTech company created to translate our scientific knowledge into molecular tests developed for the early diagnosis of gestational diseases such as preeclampsia. Our main activity is to provide innovative solutions that protect women and their children from pregnancy-related complications. We want to create a world where pregnant women do not fear for their health. IPREMOM's scientists are experts in obstetrics, biotechnology, and computational biology with a passion for improving maternal and fetal health. Position We are seeking a Computational Biologist to lead the data analysis tasks developed by iPremom, as Data Science Lead, forming part of the computational biology research team at the Carlos Simon Foundation. The candidate will focus on extracting meaningful information from extensive RNA sequencing data from human subjects, implementing predictive models from RNA sequencing data, and creating a platform of pipelines to support them. The candidate will collaborate with scientists, other professionals, and collaborators from various national and international institutions to translate the results into novel applications. Requirements Master's degree in statistics, mathematics, computer science, bioinformatics, biostatistics, or another related field Five or more years of experience (Ph.D. is a plus) manipulating data sets and building statistical models in bioinformatics or any computational/quantitative biology field. Broad experience in designing and building scalable data pipelines to reach data-driven scientific conclusions. Proficiency in statistical computer languages (Python, R) and scripting in Linux, Bash, and high-performance computing resources Knowledge of resource management with SLURM Knowledge of RNA sequencing-based transcriptomics analysis (e.G., normalization methods, differentially expressed genes, and feature selection for machine learning methods) Knowledge of a variety of machine learning techniques (e.G., clustering, decision tree learning, and artificial neural networks) and their real-world advantages/drawbacks Knowledge of advanced statistical techniques and concepts (e.G., regression, properties of distributions, and statistical testing) and experience with applications Version and project management with GitHub Experience in organizing results in reports or notebooks (e.G., Rmarkdown, Quarto, or Jupyter) Ability to organize workloads and manage competing priorities. Resolve, dynamism, and strong problem-solving skills. Desirable Skills Management, leadership, and team supervision Knowledge of pregnancy complications and other somatic conditions Knowledge of modern biological data warehouses (SRA, GEO) Experience with cloud computing platforms (AWS preferred) Additional Skills Drive to learn and master innovative technologies and techniques from next-generation sequencing applications. Experience visualizing/presenting data to collaborators


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