POSITIONS OPEN IN THE LAB AS OF JULY 2020
Two PhD Positions
- Biological nanopores for single-molecule sensing
Nanopore sensing is a powerful single-molecule approach currently developed for the precise detection of biomolecules, as for instance in DNA and protein sequencing. Our laboratory is developing this technology exploiting the properties of biological pores. Recently, we showed that aerolysin, a pore-forming toxin, exhibits high sensitivity for single-molecule detection and can be ad hoc engineered for different sensing tasks. The goal of this project is to develop and characterize aerolysin-based nanopores as sensing devices to be applied for genome sequencing, proteomic analysis and disease diagnosis. The project is highly interdisciplinary, includes experimental and computational aspects and interactions with a diverse network of collaborators. Students with a background in biochemistry, physics, bioengineering and computational sciences are encouraged to apply.
- Integrative modeling at the membrane-protein interface
Molecular interfaces are essential for the formation and regulation of all assemblies that sustain life, to define cellular boundaries and intracellular organization, and to mediate communication with the outer environment. Our laboratory has been studying the molecular mechanisms governing the association of proteins to their membrane interfaces in order to understand the functional implications of this interplay. Multiple projects are available that focus on the theoretical and computational investigation of the structural and dynamic properties of membrane protein systems. All of them are addressed in synergy with experimental collaborators to allow for an efficient integration of biochemical and biophysical data. Students with a background in biochemistry, physics, bioengineering and computational sciences are encouraged to apply.
One postdoc position in biological nanopores for single-molecule sensing
Nanopore sensing is a powerful single-molecule approach currently developed for the precise detection of biomolecules, as for instance in DNA and protein sequencing. Our laboratory is developing this technology exploiting the properties of biological pores. Recently, we showed that aerolysin, a pore-forming toxin, exhibits high sensitivity for single-molecule detection and can be ad hoc engineered for different sensing tasks. The goal of this project is to develop and characterize aerolysin-based nanopores as sensing devices to be applied for genome sequencing, proteomic analysis and disease diagnosis. The project is highly interdisciplinary, includes experimental and computational aspects and interactions with a diverse network of collaborators. The ideal candidate should hold a PhD degree from one of the following fields, biochemistry, biophysics, bioengineering, analytical chemistry or computational sciences.
EPFL is a highly international environment with English as the main language. We are located at Lausanne, next to a city has been ranked the best city in the world with a population under 200,000.
Motivated candidates are encouraged to contact Prof. Dal Peraro.
Description:
Cryo-Electron Microscopy (cryoEM) has opened unprecedented vistas in biology, offering detailed insights into macromolecular architectures. CryoEM captures snapshots of large complexes in their native configurations, enabling scientists to visualise their three-dimensional structures with unprecedented precision. However, the raw data is inherently noisy, and converting these 2D images into accurate 3D reconstructions demands meticulous postprocessing and advanced computational techniques. However, the challenge persists in dealing with various global and local resolutions and deriving precise structures from the cryoEM density maps.
Owing to the inherently dynamic nature of proteins and their potential interactions with ligands and other subunits within complex systems, the task of effectively juxtaposing experimental cryoEM data with established reference structures presents an ongoing challenge. This project aims to construct density map embeddings encapsulating the information in the voxel grid through an autoencoder and evaluate their biological meaningfulness.
Prerequisites:
We seek a motivated Master’s student, with a solid background in computer vision and deep learning, and a keen interest in addressing challenges in the realm of structural biology and protein modelling. The project is a collaboration between the Laboratory for Biomolecular Modeling (led by Prof. Dal Peraro) and the Computer Vision Laboratory (led by Prof. Fua).
Contact:
Simon Crouzet ([email protected]) and Alexandre De Skowronski ([email protected])
Reference:
Rosenbaum, D. et al. Inferring a Continuous Distribution of Atom Coordinates from Cryo-EM Images using VAEs. (2021) doi:10.48550/ARXIV.2106.14108.
Zhang, Z. et al. Protein Representation Learning by Geometric Structure Pretraining. (2022) doi:10.48550/ARXIV.2203.06125.
Research projects for master, bachelor and summer students
Mid-term projects within the existing lines of research of the lab are frequently available within the different internship schemes of the master schools. Interested students (also at the Bachelor level) can visit the Teaching section and are invited to contact Prof. Dal Peraro by email or personally at my office (AAB 048). International students at the master and bachelor level can have the opportunity to join our lab for a summer internship applying to the Summer Research Program hosted every year by the School of Life Sciences.