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- Centre for Genomic Regulation
- Universitat Pompeu Fabra
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- CRAG-Centre de Recerca Agrigenòmica
- Centre d'Estudis Demogràfics
- Institute of Chemical Research of Catalonia ICIQ
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- UNIVERSIDAD AUTÓNOMA DE MADRID
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and Education. Pre-doctoral contracts are renewed annually for up to 4 years. Renewal is subject to satisfactory performance in the PhD studies and related research activities. The gross yearly salary
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FieldBiological sciences » BiologyEducation LevelPhD or equivalent Skills/Qualifications Under the coordination and supervision of Dr J. M. Hernández Rivas, the Researcher will participate in a variety or research
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Framework Programme? HE / ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The emerging ‘Synthetic Cell Programming’ lab, led by Dr. Santos-Moreno
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Framework Programme? Not funded by an EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The emerging ‘Synthetic Cell Programming’ lab, led by Dr. Santos
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Gene Regulation You are fluent in English Desirable but not required/ Nice to have Computational Biology Skills Experience with RNA analysis Education and training You hold a BSc or master's in molecular
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their differentiation, using epimutations and single cell DNA methylation readouts (see biorxiv preprint ). The student will further develop the application of this method to human blood- ansd bone marrow samples and in
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discipling within the European Higher Education System (minimum 300 ECTS) or equivalent by October 2024 You are fluent in English Desirable but not required/ Nice to have Computational Biology Skills
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and efficiency. Key Responsibilities: Develop and implement novel machine learning algorithms for protein sequence annotation. Design and train encoder-decoder language models tailored to protein
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Higher Education System (minimum 300 ECTS) or equivalent by October 2024Strong background in protein research Experience in characterizing proteins with biophysical methods Experience with bioinformatic
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on mutation influx and in how we can identify cancer driver events from observed mutation data. To this end, we develop mathematical and computational approaches to estimate mutation rates, tumor growth