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Field
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and design nanostructures tailored for aerospace applications. About us The Division of Engineering Materials explores the relationship between technologically important materials and their properties
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are building a team with diverse scientific backgrounds to study the interaction between behavioral goals, life experience, and sensory processing. Our experiments merge a range of approaches, including large
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-quality robotics research in the areas of robot grasping and manipulation, kinematics and mechanisms, sensing, and human-robot interaction. Within CORE, SAIR focuses on multimodal machine learning for human
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the sensory coding of orofacial thermal, Chem esthetic, and taste sensations, and cross-modal and multisensory interactions between somatosensory and gustatory signals in the periphery and brain. The Lab’s work
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to promote big tau splice variant and will test these in vivo. Follows up on some of the regulators of tau that we have identified to determine precise site of interaction, and potentially design an assay
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concepts to device fabrication, measurements, data discussion and analysis. The successful candidate will interact extensively with the PI, graduate and undergraduate students. Job Duties: 35 % experiment
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and detailed research plan) Strict compliance with the MSCA mobility rule that the researcher must not have resided or carried out his/her main activity (work, studies, etc.) in the host organisation's
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modelling, innovative and carefully-designed behavioural experiments, in-silico reconstructions of animal interactions, and bio-mimetic robotic systems. You will benefit from a vibrant and inclusive research
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automation, machine learning, mobile robotics, process control, sensor processing, machine vision, and/or human machine interaction. This position will require working with external partners, corporations, and
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, including: Robot Learning: Creating algorithms that empower robots to learn autonomously from interactions and adjust to new tasks. Manipulation: Enhancing techniques for precise and adaptable object handling