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at the earliest on 1st August, 2026. The position is funded by the Marie Skłodowska-Curie Doctoral Network (MSCA-DN), on “Understanding Lipid ImmunoMetabolism to treat disease” (UNLIMITED) within the Horizon Europe
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to neuronal dysfunction and degeneration in HD. In parallel, epitranscriptomic mechanisms, particularly N6-methyladenosine (m6A) RNA methylation, have emerged as key regulators of neuronal homeostasis, but
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the analysis of aircraft-based observations, controlled laboratory experiments, and the development of advanced simulation tools. In parallel, GRAIL addresses key technological challenges, including
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, or related fields strong interest in photosynthesis, enzyme evolution, and ecophysiology good analytical skills and motivation for research proficiency in English ----- Application procedure. Interested
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de Biología Molecular Severo Ochoa (https://www.cbm.uam.es ), Madrid, Spain • Deadline for Applications: 5 May 2026 Application Process • Applicants should send a CV and a letter of motivation to
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well as amplification of genetic material by PCR. Basic data processing tools: Excel, R, Python Bioinformatics skills to process RNA-seq and ddRDASeq: demultiplexing, quality filtering, assembly, mapping; Generate de
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 3 months ago
research stay. Highly desirable: - Training or experience in Bioinformatics (Master’s degree, courses, or equivalent). What We Offer - Predoctoral contract for 2 years, extendable up to 4 years, leading to a
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letter – 10 Minimum score required to pass the selection process: 60 Selection process: A single phase of curricular evaluation and. To validate this request, you must validate the form that is accessed
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. The position is embedded within a multidisciplinary team focused on understanding the relationships between food structure, bioactive and technological function, and transformation processes, from
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and Drug Delivery Systems for Enhanced Bone Regeneration” (Reference: PROID2025010017). This project focuses on the optimization of additive manufacturing processes (MEX) and scaffold performance