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• Claas ABERT - Physics-Constrained Magnetization Reconstruction for Magnetic Imaging

  This project aims to advance magnetic imaging by developing a novel computational framework for reconstructing magnetization configurations. This will be achieved by applying inverse micromagnetics, using the NeuralMag software, to incorporate physics-motivated constraints.
  NeuralMag is a Python library for micromagnetic simulations that uses machine learning frameworks for efficient tensor operations and implements a nodal finite-difference discretization scheme for improved accuracy.

  
  The project aims to enhance the accuracy and resolution of magnetic imaging by integrating physics-based constraints, enabling detailed analysis of magnetic structures. The successful completion of the project will contribute to the development of high-resolution imaging of magnetic textures and the mapping of complex magnetization dynamics.

  https://gitlab.com/neuralmag/neuralmag
• Luca BANSZERUS - Cooper Pair Splitters in Bilayer Graphene

  Experimental internship

  Description: Bilayer graphene, a fascinating two-dimensional material, provides a highly tunable platform to study unconventional superconductivity and quantum transport at the nanoscale. One exciting research direction is the realization of Cooper pair splitters - devices that spatially separate electrons from superconducting Cooper pairs, creating spin- and valley-entangled electrons. Such devices are essential for applications in quantum computing, secure quantum communication, and fundamental studies of quantum entanglement. During the VDSP internship, you will actively participate in fabricating and characterizing gate-defined quantum dot structures in bilayer graphene. You will gain hands-on experience with cutting-edge nanofabrication techniques, van der Waals stacking, device design. Furthermore, you will learn to conduct low-temperature electrical transport measurements, analyzing how Cooper pair splitting efficiency depends on magnetic fields, gate voltages, and temperature.As an intern, you will be fully integreated into our research group and you will develop a solid foundation in quantum device physics and quantum transport phenomena, while contributing directly to ongoing research efforts in the Quantum Transport Lab at the University of Vienna. 

  Website: https://quantumtransport.univie.ac.at/
• Luca BANSZERUS - Valley-Chiral Transport in one-dimensional topological channels in Bilayer Graphene

  Experimental internship

  Description: Bernal-stacked bilayer graphene provides an exceptional platform to investigate 1D topological electronic states known as "kink states,” which emerge at domain boundaries of oppositely gated regions of the device. These kink states exhibit valley-chiral transport, meaning electrons propagate in directions determined by their valley quantum numbers, making them attractive candidates for future quantum electronic devices based on valleytronics. The VDSP internship will focus on experimentally realizing and characterizing gate-defined kink states in bilayer graphene. The intern will actively participate in device fabrication using state-of-the-art nanofabrication techniques, and precise van der Waals stacking. Furthermore, the intern will perform low-temperature quantum transport measurements to study valley-chiral transport properties and evaluate the efficiency of kink states as valley filters and valves.As an intern, you will be fully integreated into our research group and you will gain extensive hands-on laboratory experience, and direct engagement with advanced quantum transport experiments. Participants will gain deep insights into valleytronics and quantum phenomena, while making meaningful contributions to the groundbreaking research at the Quantum Transport Lab.

  Website: https://quantumtransport.univie.ac.at/
• Roberto CERBINO - Probing fluctuation-induced forces in non-equilibrium fluids

  Experimental internship

  Description: Casimir forces emerge when fluctuating fields are confined, as seen between uncharged, conducting plates in a vacuum or in fluids near a critical point. Out-of-equilibrium fluids exhibit even stronger fluctuations, which theory predicts should generate remarkably large Casimir-like forces in confined spaces. However, measuring these forces experimentally remains a challenge. In this project, we aim to overcome this barrier by using advanced optical techniques to track the interactions of colloidal particles suspended in a complex medium with giant fluctuations driven by diffusion or thermophoresis. Our goal is to provide the first direct experimental evidence of non-equilibrium Casimir-like forces - offering exciting new insights into fluctuation-induced interactions in soft matter physics.

  Group website: https://somexlab.github.io/
• Borivoje DAKIC - Macroscopic Entanglement in Atomic Ensembles

  Project Description: This is a theory project that builds on two theoretical results, where the framework for macroscopic superpositions has been established [1,2]. The main goal is to extend these developments into an operational setting using atomic ensembles and to devise a theoretical proposal to measure quantum correlations by means of atomic interferometry.

  [1] Miguel Gallego, Borivoje Dakić, Macroscopically nonlocal quantum correlations,  Phys. Rev. Lett. 127, 120401 (2021)
  [2] Miguel Gallego, Borivoje Dakić, Quantum theory at the macroscopic scale, arXiv:2409.03001, 2024.

   

  Requirements: Excellent knowledge of linear algebra, statistics, quantum mechanics, quantum optics, quantum interferometry, and elements of quantum information.

  https://dakic.univie.ac.at/
• Thomas JUFFMANN - Super-resolution microscopy based on elastic scattering

  Experimental internship

  Microscopy techniques based on elastic light scattering are powerful tools for studying nanoscale objects. Detecting the scattered light of metal nanoparticles or single proteins led to applications like the ultrafast tracking of dynamics on cell walls or mass photometry. Unlike fluorescence microscopy, elastic scattering offers high scattering rates, low phototoxicity, and avoids bleaching. However, it lacks specificity and the internal-level structure supporting super-resolution microscopy. Consequently, the spatial resolution is limited by the excitation wavelength. You will join a team that aims to overcome this limit.

   

  https://imaging.univie.ac.at/
• Jonas RIES - Quantitative analysis of the molecular architecture of muscle cells using super-resolution microscopy

   

  Please note: this internship position is not financed via the VDSP. For further inquiries regarding the position please contact Prof. Ries: jonas.ries@univie.ac.at

   

  About the position

  This theoretical Master’s internship is part of a research project that uses super-resolution microscopy to understand how muscle cells produce force. We are studying the molecular machines that drive force generation and how they are assembled into an ordered structure. To assist in understanding this structure, we have created a theoretical model of muscle fibers, based on literature data. This model generates synthetic super-resolution images, which serve as control datasets to validate and optimize our analytical pipeline. We are looking for a student to expand this model and develop statistical tools to compare theoretical results to experimental super-resolution data.

   

  Candidates

  We are looking for a highly motivated candidate with strong experience in coding, preferably in Python, and an interest in biology. Experience with image and/or point cloud analysis is a plus. Training and supervision will be provided throughout the project, but we also expect a high level of drive and independence. Excellent spoken and written English skills are required.

   

  About the lab

  The Ries lab is developing super-resolution microscopy methods for structural cell biology. Our group combines expertise in advanced microscopy, computational image analysis, and molecular cell biology to study cellular architecture at the nanoscale. We work in a highly interdisciplinary environment, bringing together physicists, computational scientists, and biologists to push the boundaries of imaging technology and its applications. A key aspect of our research involves leveraging artificial intelligence and machine learning for image reconstruction, data analysis, and extracting quantitative information from large-scale super-resolution datasets. For this project, the candidate will be co-supervised by a postdoctoral researcher specializing in computational science and another with a background in biology, ensuring a comprehensive approach that integrates both experimental and analytical perspectives.

   

  Application

  Your application should include a concise description of research experience, a list of published articles and contact details for three references.