Are you holding Master’s degree and looking for fully funded PhD positions? German Electron Synchrotron DESY, Germany invites online application for multiple funded PhD Programs / fully funded PhD positions in various research areas.
Candidates interested in fully funded PhD positions can check the details and may apply as soon as possible. Interested and eligible applicants may submit their online application for PhD programs via the University’s Online Application Portal.
1. Fully Funded PhD Position in Large Peptide Aggregation Models for Structural Modelling of Protein Aggregation
Summary of PhD Program:
Protein misfolding diseases, e.g., Alzheimer’s or Parkinson’s, are accompanied by aggregates of peptides (e.g., amyloid fibrils), which acquire varied three-dimensional (3D) structural configurations. Such fibrils are not limited to human diseases but are also found across the tree of life, perhaps originating in the prebiotic era. Different 3D structural configurations of fibrils correlate with distinct biological activities. For example, the cross-α fibril structure of the peptide uperin 3.5 (secreted by Australian toadlet) has a protective role against bacterial infections.
Application Deadline: Open until filled
2. Fully Funded PhD Position in Building Robust and Calibrated Generative Models to Detect Anomalies in Data
Summary of PhD Program:
Despite an impressive and extensive effort by the Large Hadron Collider (LHC) collaborations at CERN, currently, there is no convincing evidence for new particles produced in high-energy collisions. However, the Standard Model cannot be the final theory of nature. Past years have seen an enormous increase in anomaly-based strategies to search for new physics, such as the weakly supervised CATHODE approach co-developed in Hamburg. A key ingredient in this approach is training a generative model to learn an in-situ model of the background data.
Application Deadline: Open until filled
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3. Fully Funded PhD Position in Design of Seismic Newtonian Noise Cancellation Systems by Neural Network Enhanced Simulations
Summary of PhD Program:
Are you passionate about cutting-edge research in simulations for seismic wave propagation in gravitational wave detectors? This project focuses on developing advanced Newtonian Noise Cancellation (NNC) systems for gravitational wave detectors designed to observe spacetime variations from cosmic events like black hole collisions. Newtonian noise, arising from mass density changes caused by seismic waves, poses significant challenges to these detectors, even those planned to be situated in a quiet underground, like the Einstein Telescope. Our project aims to enhance NNC systems by integrating advanced neural network-enhanced simulations and modern fiber optic strain sensors.
Application Deadline: Open until filled
4. Fully Funded PhD Position in Phase Retrieval in Imaging and Speech Enhancement (PRISE)
Summary of PhD Program:
Advanced sources such as free-electron lasers produce intense and coherent beams of X-rays, opening up new possibilities to image biological materials, such as single molecules, at atomic resolution. Since atomic resolution lenses do not exist, such methods usually rely upon retrieving the structural information encoded in the far-field coherent diffraction pattern [1]. This intensity pattern corresponds to the Fourier magnitude of the object and is thus an incomplete measurement since the phase of the diffracted wave cannot be measured. The missing phase information needs to be retrieved to reconstruct the original structure.
Application Deadline: Open until filled
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5. Fully Funded PhD Position in Coherence-Based X-Ray Microscopy: Automated Tuning and Uncertainty Quantification
Summary of PhD Program:
X-ray microscopy at large-scale facilities enables studying a wide range of specimens, from single cells to small animals or from single crystals to bulk materials in working conditions. To realize this and to make these methods available to the growing user community of synchrotron radiation sources, our methods must also grow. The imaging methods employed to assess these samples are based on coherent lens-less microscopy. Therefore, the image of the sample is not formed during the measurement process itself but using a reconstruction algorithm. The algorithm solves a so-called ill-posed inverse problem whereby a complex wavefield is recovered from an intensity-only measurement.
Application Deadline: Open until filled
6. Fully Funded PhD Position in Towards the Accelerator Metaverse: Spatial Computing Interfaces for Crossmodal Human-Robot Collaboration in Accelerators
Summary of PhD Program:
Robot technology, spatial computing, and extended reality (XR) have shown enormous potential to significantly enhance the operation, monitoring, repair, and maintenance of accelerators and their infrastructure, facilitating more efficient user experiments. In particular, advancements in artificial intelligence (AI), such as natural language processing (NLP) or eye and hand tracking, enable the combination of multiple interaction modalities such as speech, gaze, and gestures for such robot control. Moreover, instead of focusing on low-level tasks such as using the hands for navigation control, users could guide robots with simple verbal instructions or gestures, e.g., looking at an object and performing an air tap to make the robot locomote semi-autonomously toward the intended object.
Application Deadline: Open until filled
7. Fully Funded PhD Position in Semi-Automatic 3D Reconstruction Processes for Stereoscopic Hard X-Ray Microscopy
Summary of PhD Program:
The proposed thesis aims to develop a semi-automatic interactive 3D reconstruction process for materials in stereoscopic hard X-ray microscopy. As a starting point, we will focus on microchips, with the aim to differentiate between electronic layers based on distinctive shapes and material properties and extend this approach to other sample types. Integrating human expertise and deep learning methods could enhance the 3D reconstruction process and enable more efficient automated reconstruction workflows.
Application Deadline: Open until filled
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8. Fully Funded PhD Position in Machine Learning and Time Domain Methods for Simulations in Nonlinear Optics
Summary of PhD Program:
Nonlinear optical processes often rely on the slowly varying envelope approximation, assuming only narrowband optical signals that interact with each other over perturbative optical nonlinearities. However, many modern optical processes, such as continuum generation in nonlinear waveguides or THz generation, often cover multiple octaves of bandwidth. This broad bandwidth asks for the direct simulation of the electric field, including the carrier wave. It becomes even more demanding when carrier-envelope phase-sensitive effects are relevant.
Application Deadline: Open until filled
9. Fully Funded PhD Position in Hardware-Portable Data Analysis Building Blocks for the High Luminosity LHC Era
Summary of PhD Program:
In the present project, we attempt to explore and investigate hardware-portable ecosystems such as ALPAKA and KOKKOS for HL-LHC data analyses. The outcome will allow us to learn which ecosystem is best suited for expected analyses. Furthermore, it will elucidate which related data access patterns exist within the respective data handling routines and which will benefit from accelerators. A subset of the identified patterns shall be implemented using one of these hardware-portable ecosystems and, as building blocks, be provided to the community – a starting point for sustainable, hardware-portable HPC-aware software building blocks in HL-LHC data analysis.
Application Deadline: Open until filled
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10. Fully Funded PhD Position in Combined Reconstruction Approach for Holotomography: Joint Phase Retrieval and Tomography
Summary of PhD Program:
The project aims to generalize the two-step reconstruction procedure to a joint reconstruction. The goal is to consider all intensity measurements simultaneously and to use the 3D consistency as an additional constraint to perform the phase retrieval directly on the tomogram. It is necessary to investigate several subproblems to solve this task. A new inverse problem has to be formulated, a suitable solver has to be found, and a rigid motion model of the object’s movement during the data acquisition needs to be used.
Application Deadline: Open until filled
11. Fully Funded PhD Position in Top Quark Reconstruction with Generative Models for Searches for Heavy Higgs Bosons and Top-Antitop Quark Bound States with the CMS Experiment
Summary of PhD Program:
In this project, we investigate an intriguing excess observed in the production of top-antitop quark pairs (tt) initially identified during our DASHH search for heavy Higgs bosons with the CMS experiment. The aim is to determine whether this deviation arises from physics beyond the SM or if it can be attributed to a tt bound state. While bound states have been detected for all five lighter quark types, such states, called toponium, have yet to be observed for the heaviest of all elementary particles, the top quark.
Application Deadline: Open until filled
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12. Fully Funded PhD Position in AI-Powered XFEL Laser Operations: Boosting Uptime with Language Models
Summary of PhD Program:
The operation of large-scale X-ray synchrotrons and free-electron lasers (XFELs) relies on various complex optical laser systems. Beamtime at those facilities is precious; laser failures can cause costly downtime. Even though a laser operator is on-call at all times, it is difficult for a single person to know all the details of every laser system. This project tackles this challenge by developing a novel artificial intelligence-powered assistant to aid on-call laser operators with troubleshooting and maintaining facility laser systems. This project will adjust and further develop advanced large language models (LLMs) to process extensive technical documentation, logbook entries, and control system data to provide expert-level assistance to laser operators.
