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• Claas ABERT - Inverse Problems in Theoretical Magnetism using Machine Learning

  This internship focuses on solving inverse problems in theoretical magnetism using modern machine learning methods. Topics include topology optimization of magnetic nano-devices, parameter inference, and magnetization reconstruction based on physical constraints.
  
  The work builds on NeuralMag [1], a Python-based micromagnetic simulation framework that uses JAX for efficient tensor operations, automatic differentiation, and gradient-based optimization.
  
  The project offers hands-on experience at the intersection of computational magnetism, numerical modeling, and machine learning, contributing to the development of next-generation tools for the inverse design of magnetic systems, see e.g. [2].

  [1] https://neuralmag.gitlab.io/
  [2] https://www.nature.com/articles/s44306-025-00082-3
• Markus ARNDT - Methods for Universal Matter-Wave Interferometry

  Our group is pursuing matter-wave research with molecules, clusters and nanoparticles, aiming at pushing the experimental limits of quantum physics to the extremes and testing the transition to classical phenomena.

  In this endeavor we offer the possibility for ambitious and talented experimentalists after the 4^th year of their physics studies to be integrated into our research group as an intern for 2-6 months.  Depending on the expertise and interest, the placement will be chosen to be with the cluster, protein or nanoparticle team.

  Among the most important practical challenges in such an internship we will address new source and detection developments.

  Website: https://www.quantumnano.at/
• Markus ARNDT - Superconducting nanowire detectors for molecular physics and physical chemistry

  Superconducting nanowires have been developed over the last 25 years primarily as single photon detectors with applications in quantum optics, quantum information, astronomy, LIDAR or photon correlation microscopy.

  Our team, together with our European partners, are exploring new applications in low-energy mass spectrometry and molecular science and we offer an internship of 2-6 months for  a capable and ambitious person after their 4^th year of physics studies to help us develop these application further.

  Website: https://www.quantumnano.at/
• Luca BANSZERUS - Proximity-Superconductivity in bilayer graphene quantum dots

  Bilayer graphene, a highly tunable two-dimensional material, provides an interesting platform for exploring quantum transport and realizing superconductor/semiconductor hybrid devices.

  In this project, you will join our efforts to investigate gate-defined quantum dots strongly coupled to superconducting leads, a regime at the interplay of electron correlations, quantum confinement, and superconducting pairing. Such hybrid quantum dots are the fundamental building blocks for Cooper pair splitters, artificial topological systems and novel types of superconducting hybrid qubits. 

  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 quantum dot spectra depend on magnetic fields, gate voltages, and temperature.

  As an intern, you will be fully integrated 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. 

   

  The time frame is flexible. The duration should preferably be between 4-6 months. 

   

  Group website: https://quantumtransport.univie.ac.at/

   

   
• Roberto CERBINO - Expanding Differential Dynamic Microscopy

  Experimental and/or computational internship
  
  Time frame: Flexible between March and December 2026 (2–6 months)
  
  Description: Differential Dynamic Microscopy (DDM) combines real-space imaging and light scattering to quantify microscopic dynamics in soft and biological materials. While DDM has become a powerful and widely adopted technique, new challenges arise when imaging complex systems where scattering becomes multiple or dynamics are heterogeneous.

  In this project, students will contribute to extending DDM along one (or more) of several cutting-edge directions:

  1. developing optical and computational approaches to handle multiple scattering and extract meaningful dynamic information from optically dense samples;
  2. implementing and benchmarking AI-based pipelines for automated data analysis and feature extraction;
  3. designing novel experimental protocols that connect microscopy, rheology, and statistical physics.

  Depending on their background, students may focus on instrumentation, coding, or data interpretation. The project combines hands-on experience in optical microscopy with data analysis and offers immersion in a vibrant interdisciplinary environment at the interface between physics, materials science, and machine learning.
  
  Group website: https://somexlab.github.io/
• Cesare FRANCHINI - Charge doped altermagnets: polarons and symmetry

  Type: Theoretical and computational

  Information regarding the respective field/project:

  Altermagnetism has emerged as a new paradigm in magnetism, distinct from the traditional classification into ferromagnetism and antiferromagnetism [1]. In this project, the intern will employ first-principles calculations and symmetry analysis to investigate how altermagnetic properties evolve under charge doping, with the goal of uncovering a possible coupling between polaronic excess charge [2] and the underlying altermagnetic order, conisdering boith bulk and surface phases.

   

  [1] https://journals.aps.org/prx/abstract/10.1103/PhysRevX.12.040501

  [2] https://www.nature.com/articles/s41578-021-00289-w
• Cesare FRANCHINI - Machine learning excitonic properties

  Type: Theoretical and computational

  Information regarding the respective field/project:

  The objective of this project is to develop a machine learning (ML) framework capable of predicting the excitonic properties of real materials based on first-principles Bethe-Salpeter equation (BSE) calculations. The project will begin with the generation of a high-quality database of excitonic observables obtained through high-throughput BSE computations [1]. In the second phase, transfer learning algorithms will be implemented to efficiently predict average dielectric properties from this dataset [2,3]. Time permitting, the intern will also explore the implementation of an equivariant neural network to predict the full dielectric tensor, building on recent developments in data-driven dielectric function modeling.

   

  References relevant for the project:

  [1] https://doi.org/10.48550/arXiv.2410.15948

  [2] https://www.nature.com/articles/s41467-025-63355-9

  [3] https://journals.aps.org/prmaterials/abstract/10.1103/PhysRevMaterials.8.L122201
• Thomas JUFFMANN - Colibri: Combining lifetime measurements with brilliant imaging:

  Fluorescence lifetime microscopy yields information about the local environment of a fluorophore (pH, binding partners, ion concentration…), which is crucial for analyzing the metabolic state of cells and tissue. We have built a detector that can measure fluorescence lifetimes orders of magnitude faster than previously possible. This enables combining lifetime measurements with other advanced microscopy techniques such as light-sheet or super-resolution microscopy. You will work in close collaboration with biologists in order to optimize our lifetime detector for specific life-science applications.

  Website: https://imaging.univie.ac.at/ 
• Thomas JUFFMANN - Label-free super-resolution microscopy

  Optical microscopy is typically limited to a spatial resolution given by the wavelength of light. Super-resolution microscopy overcomes this limit, building on the level structure of fluorescent labels. We aim to demonstrate label-free super-resolution microscopy techniques, e.g. by harnessing optical near-fields as in optical near-field electron microscopy. You will be working in a team of physicists to enable nanometric resolution in applications ranging from electrochemistry to biophysics.

  Website: https://imaging.univie.ac.at/
• Christos N. LIKOS - Conformations and associations of flower-like coacervate micelles

  Computational and Soft Matter Physics

  Project description:

  In this project, we will be investigating by means of computer simulation the properties of micellar aggregates formed by ABA triblock copolymers, with charged A blocks and water- soluble B-blocks, in an aqueous solvent containing an oppositely charged homopolymer [1,2]. Under these conditions, the ABA triblocks attached to the homopolymer, which forms the core of reconfigurable flower-like micelles, in which the anchored polymer forms a closed loop. Our aim is to examine the conformations and aggregation of single micellar molecules as well as the reorganization of the adsorption scenarios once two of them are close to one another, allowing the formation of reversible bridges among the two. The project has immediate applications in the understanding of the properties of polymer-mediated macroscopic gels and the nonlinear elasticity of the same [3].

   

  [1] M. Lemmers, J. Sparkel, I. K. Voets, J. van der Gucht, and M. A. Cohen Stuart, Angewandte Chemie 122, 720 – 723 (2010).

  [2] M. Lemmers, I. K. Voets, M. A. Cohen Stuart and J. van der Gucht, Soft Mater 7, 1378 – 1389 (2011).

  [3] P. I. Hurtado, L. Berthier, and W. Kob, Phys. Rev. Lett. 98, 135503 (2007).
• Thomas PICHLER - Unravelling the optical and vibronic response of transition metal dichalcogenides via Inelastic scattering

  The internship is an experimental work to get a basic understanding of the underlying optical and vibronic properties using either resonance Raman spectroscopy or momentum resolved inelastic electron spectroscopy in a unique electron microscope nanospectrometer (MORE-TEM).

  The successful candidate will work together with experienced PhD students and Postdocs on these layered 2D systems. 

  Website: https://epm.univie.ac.at/ 
• Josef PRADLER - Early universe particle production of sterile states

  The project encompasses various aspects of particle production in the early Universe. Depending on the particle candidate under consideration, the generation channels can be of purely gravitational nature or mediated by interactions with dark matter and/or Standard Model particles. Bounds will be placed on the existence and coupling strengths of particles that are neutral under the Standard Model gauge group, hence "sterile," by utilizing cosmological, laboratory and/or astrophysical probes.

  Website: https://particle.univie.ac.at/research/projects/student-projects/proj-detail/news/early-universe-particle-production-of-sterile-states/ 
• Hidetsugu SHIOZAWA - Exploration of the Physical Properties and Applications of Metal-Organic Frameworks

  Project description:

  This project centers on metal-organic frameworks (MOFs), with a focus on experimental approaches. It primarily involves synthesis, structural and spectroscopic characterization, and the interpretation of experimental data, complemented by density functional theory (DFT) calculations.

  The research is motivated by potential applications of MOFs in areas such as single-photon emission, light-emitting devices (LEDs), energy storage (including ion batteries and hydrogen storage), and catalysis for water splitting. Depending on the candidate’s skills, experience, and interests, the scope can be tailored to focus on one or more of these areas, offering a flexible and personalized approach aligned with the available time and individual background.
  
  https://homepage.univie.ac.at/hidetsugu.shiozawa
• Dieter SÜSS - Computing Vortex Entry and Exit Barriers in Type-II Superconductors Using the String Method

  Theoretical - Physics of Functional Materials

  Type-II superconductors exhibit quantized vortices whose creation and annihilation at sample boundaries determine critical currents, magnetic hysteresis, and noise in superconducting devices.

  The goal of this internship is to implement the string method to compute the minimum-energy paths and energy barriers for vortex entry and exit using the Ginzburg–Landau (GL) free-energy functional. Within this work one will Implement the string method for the GL equations in two dimensions. Compute the minimum-energy paths between metastable vortex configurations. Quantify the energy barriers for vortex creation and annihilation at boundaries.

  Understanding how vortices penetrate or leave a superconductor is crucial for improving the stability and performance of superconducting films, sensors, and quantum devices. The calculated barriers will clarify the role of surface and geometric effects in vortex dynamics and help guide the design of materials with controlled flux entry.

  Website: https://fun.univie.ac.at/
• Toma SUSI - Simulating transmission electron microscopy of tilted ionic materials

  Project description

  Transmission electron microscopy (TEM) image simulations are often based on independent atoms, which are a poor description for ionic materials with significant charge transfer. Although these can be treated with density functional theory, it is beneficial to parametrize ionic potentials to enable easier and faster simulations, especially for otherwise intractable tilted specimens.

  Building on prior work, the project is to test the existing ionic potential implementation for tilted specimen in our open-source code abTEM, and thus experience with Python is necessary and experience with TEM desirable.

  Website: https://physnano.univie.ac.at/research/topics/topics-details/news/transmission-electron-microscopy-from-first-principles/ 
• Andreas ZÖTTL - Hydrodynamic effects in active polymers

  Project description

  Different polymeric and filamentous biological materials which are out of equilibrium can be described as active polymers. A simple numerical model consists of chains of N beads connected by springs. In passive polymers beads move according to internal forces as well as to Brownian motion because of their typically small size.

   

  In the proposed project, a polymer is made active by applying tangential forces to the polymer. Overall the active polymer is force- and torque free, realized by applying counter-forces to the surrounding fluid (see Fig. 1). The fluid is here modeled explicitly by effective fluid particles which interact with each other via a multiparticle collision dynamics (MPCD). This ensures that hydrodynamic interactions between the beads are accounted for automatically. The project directly builds on our preliminary studies on hydrodynamic effects in active polymers [1].

  A major goal of the project is to investigate by means of computer simulations how hydrodynamic interactions

  influence the dynamic and static properties of the active polymers, by tuning the length N of the polymers and the strength of the activity in comparison to thermal noise. The investigations of this project are of direct relevance to better understand how activity and hydrodynamic effects determine polymer properties, which may be used to better understand active polymer properties such as in DNA fragments, filamentous bacteria and swimming worms. 

  [1] L. Sappl, C. N. Likos, and A. Zöttl, Locally tuned hydrodynamics of active polymer chains, arXiv preprint arXiv:2508.18789 (2025). doi.org/10.48550/arXiv.2508.18789

  Website: https://homepage.univie.ac.at/andreas.zoettl