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mathematics) or should be close to submitting their PhD thesis. They should also have experience in handling longitudinal data and conducting microsimulation or agent-based modelling. Good communication and
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in sensitive contexts, such as cybersecurity. Then, based on the knowledge acquired, they should conduct state-of-the-art research on defence mechanisms, methodologies, and tools, assessing
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on the development of a 4D injectable hydrogels for the treatment of deep wounds; so-called tunnel wounds. The CRMD team will be responsible for the design and development of peptide-based nanocarriers
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. Proven expertise in AI/ML for systems or hardware co-design, including use of reinforcement learning, LLMs, graph-based optimization, or agentic AI. Familiarity with security concepts and cryptographic
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, Biochemistry, and be enrolled in a PhD or a non-degree course, relevant for the development of the activities included in the project. Knowledge in different cell culture models (e.g. cell lines, primary
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: Recommender system for biological control agents against plant pathogens”, “2023.14580.PEX”, ”DOI: https://doi.org/10.54499/2023.14580.PEX ”, funded by the Fundação para a Ciência e a Tecnologia, I.P. through
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platforms incorporating therapeutic agents (e.g., nucleic acids, small molecules, peptides), involving mRNA for gene therapy. In the context of this project, the group of Vectors, Gene and Cell Therapy
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Language Model (LLM) Strong biostatistics knowledge including survival analysis and causal inference Experience with reinforcement learning, agentic AI systems and autonomous decision-making frameworks Data
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agents and treatment combinations in cancer models. Manage and maintain mouse xenograft models (including PDX and cell-line derived models). Perform drug administration, tumor measurement, sample
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responsibilities include: Generation of phenotype-specific networks from bulk-RNAseq and scRNAseq data from rare disease patients Building executable models (Boolean, ODE, agent-based or others) from omics data