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CGIAR, including CIMMYT and National Agricultural Research Systems (NARES). In this role, you will develop an analytical decision-support tool that integrates quantitative genetic modelling, artificial
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large-scale genomic, phenotypic, environmental, and field trial datasets, you will benchmark AI and quantitative genetics methods, develop multimodal and hybrid modelling frameworks, and investigate
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mathematical theories that connect geometric models of physical systems with new computational representations suitable for Digital Twins and future computing architectures. The project offers substantial
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you eager to accelerate the energy transition by making green
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | 3 months ago
engineering, computational biology, computer science, or a related field by the start date; strong research background in experimental biology, stem cell biology, mammalian model systems, computational biology
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, supported by Large Language Models (LLMs). Mandatory requirements: The candidate must hold a Ph.D. in Computer Science or a closely related field. Desirable requirements: Experience in Information Retrieval
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engineering, transport planning, transport modelling, mathematics, statistics, data science, economics, computer science, or a closely related discipline, or equivalent research, industrial, or commercial
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they promote translocation biogenesis, and testing them in preclinical models. The work combines CRISPR engineering of B cells, protein biochemistry and genomics approaches including RT measurements, replication
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; • Familiarity with statistical analyses and modeling as well as machine learning approaches, supported with strong skills in computational optimization of methods; • Experience working with large-scale datasets
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for malaria and other neglected tropical diseases. This will be done by developing mathematical and statistical models, to describe the time course of drug concentrations and effect. You will work closely with