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of Researchers . Please, check out our Recruitment Policy The role We are seeking a highly motivated bioinformatician to join the Evolutionary Processes Modeling group. The selected candidate will be responsible
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bioinformatician to join the Evolutionary Processes Modeling group. The selected candidate will be responsible for the analysis of DNA sequencing data derived from a unique cohort of animal tumors. Responsibilities
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, Telecommunication Engineering, or a related field with a strong academic background in Machine learning, Natural Language Processing, and/or Software Development. Applicants with an experience in one or more of the
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) LanguagesSPANISHLevelMother Tongue LanguagesENGLISHLevelExcellent Research FieldOther Additional Information Benefits The salary will be that established in the Collective Bargaining Agreement of the group of companies
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field with a strong academic background in Machine learning, Natural Language Processing, and/or Software Development. Applicants with an experience in one or more of the above academic fields are
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with a strong academic background in Machine learning, Natural Language Processing, and/or Software Development. Applicants with an experience in one or more of the above academic fields are encouraged
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Tongue LanguagesENGLISHLevelExcellent Additional Information Selection process Las personas interesadas deberán aplicar en la web de la UCM https://www.ucm.es/personal-contratado-de-actividades-cientifico
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. LanguagesSPANISHLevelMother Tongue LanguagesENGLISHLevelExcellent Additional Information Benefits 1841,92 €/monthly gross salary Selection process Applications to this offer must compulsory be registered through the online
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/interventions, and clinical diagnoses. The post would be suitable for applicants with general interests in AI, machine learning, large language models, foundation models, signal processing, computational
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of artificial intelligence (AI) and biomedical engineering. Research directions include deep learning, natural language processing, brain–computer interfaces, and their applications in disease prediction, drug