Predoctoral researcher in Liquid Phase TEM imaging of misfolded proteins at the Molecular Bionics Research group. Proyecto de Generación de Conocimiento 2022 by the Spanish Ministry of Science and Innovation

Introduction to the vacant position:

Dementia, including Alzheimer’s, Lewy body Parkinson’s, and others, is a growing health concern worldwide. These conditions are often associated with the formation and aggregation of neurotoxic misfolded oligomers such as amyloid-β, tau proteins, and α-synucleins. Understanding these harmful oligomers is essential to uncovering the molecular basis of these diseases. To investigate the protein aggregation dynamics and liquid-liquid phase separations, this project will use advanced TEM imaging in Liquid Phase. The research focuses on proteins associated with Alzheimer’s and Parkinson’s diseases, using a combination of simulations and liquid TEM imaging. Additionally, the project explores the impact of drugs and aggregation inhibitors on protein structures in liquid environments.

This interdisciplinary approach combines imaging science, physics, molecular engineering, and computational science and holds great promise for helping to create innovative treatments for neurodegenerative diseases causing dementia.We welcome individuals willing to combine experimental imaging with computational efforts. This is an exciting opportunity to be part of the Molecular Bionics group, a dynamic multidisciplinary team comprising chemists, physicists, mathematicians, engineers, and biologists. To learn more about our work, please visit our external website at https://www.molecularbionics.org.

This fellowship is associated to the research project Generación de Conocimiento, funded by the Spanish Ministry of Science and Innovation.

Main tasks and responsibilities of the successful candidate will be:
• Protein structure characterisation by standard methods
• Protein imaging by solid state and Liquid Phase TEM.
• Design and implementation of novel imaging protocols for proteins in Liquid Phase TEM
• Image analysis
• Molecular modelling simulations
• Coding experiences, particularly in handling deep learning and other machine learning techniques.
• Handling of soft materials and polymers.
• To contribute to the drafting and submitting of papers to peer reviewed journals.