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Field
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anticipation. Unlike static distributions, these models should represent the spatiotemporal transition functions of human states—predicting how a person will move or interact with objects(/persons) based
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of Spanish (not required but valued for teaching and policy dissemination in Spain). Experience with AI-based research workflows, machine learning techniques applied to financial data, or modern
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experience in microscopy-based analysis of protein condensates formed through liquid-liquid phase separation. Advantageous: Experience in RNAseq and cellular thermal shift assays. Competencies and Skills: We
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assisting with in-situ TEM measurements, facilitating cutting-edge research in sustainability and energy fields. Part of the project will also include the development of deep learning frameworks for TEM image
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required, particularly with experience in the development and design of biosensors. · Personal Competences: Proven reputation based on research excellence in their field. Positive contribution
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and modelling of omics, clinical and imaging data, development of reproducible pipelines, application of machine learning techniques, integration of multi-modal data, scientific publication and
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team. A strong interest in sustainability, resource management, and the energy transition. Terms of employment This is a full-time postdoctoral position for one year. The position is based in Santander
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environment, free from any form of discrimination-whether based on gender, sexual orientation, gender identity, age, origin, culture, religion, disability, or any other personal or social condition. We
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employees during the duration of the contract. - Two-year position based in Madrid (Spain), with a mid-term review at the end of the first year. The post is expected to run from June 2026 to June 2028. - A
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2DFERROPLEX, contributing to the development of all-optical neuromorphic components based on two-dimensional ferroelectric heterostructures. Key responsibilities include: Development, preparation, and