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PhD-Position: Towards a Universal, Data-Agnostic Framework for Automatic Anomaly Detection in Complex Multivariate Time-Series

PhD-Position: Towards a Universal, Data-Agnostic Framework for Automatic Anomaly Detection in Complex Multivariate Time-Series

PhD-Position: Towards a Universal, Data-Agnostic Framework for Automatic Anomaly Detection in Complex Multivariate Time-Series

PhD-Position: Towards a Universal, Data-Agnostic Framework for Automatic Anomaly Detection in Complex Multivariate Time-Series

Deutsches Elektronen-Synchrotron DESY

Forschung

Hamburg

  • Art der Anstellung: Teilzeit
  • 52.500 € – 70.500 € (von XING geschätzt)
  • Vor Ort
  • Aktiv auf der Suche

PhD-Position: Towards a Universal, Data-Agnostic Framework for Automatic Anomaly Detection in Complex Multivariate Time-Series

Über diesen Job

  • Anomaly Detection in Complex Multivariate Time-Series

Towards a Universal, Data-Agnostic Framework for Automatic Anomaly Detection in Complex Multivariate Time-Series

Supervisors: Prof. Annika Eichler (DESY, TUHH), Prof. Sarah Hallerberg (HAW), Dr. Nahal Sharafi (DESY, HAW)

Precise real-time detection of irregular behavior in highly complex systems is a cross-cutting challenge in accelerator physics, high-energy experiments, and large-scale industrial processes. Yet, most data streams collected at research facilities such as DESY and larger economic entities are unlabeled, noisy, and heterogeneous. This project attempts to develop and evaluate a data-agnostic, automatic anomaly-detection framework. It aims to unify state-of-the-art forecasting, reconstruction, and representation paradigms. Furthermore, it will deliver actionable uncertainty estimates and can adapt seamlessly to other domains.

Three contrasting data sets will anchor the research and development in increasing order of difficulty: (1) Optical Synchronisation System (OSS) sensor traces from DESY (rich understanding, labeled and part of prior DASHH projects); (2) SuperKEKB beam-diagnostics data from KEK, Japan (partial labels, language & coordination barriers); and (3) Economic transactional data (heterogeneous, exogenous shocks, non-physical process). Dataset 1 serves as the basis for development; Datasets 2–3 function as harder additional datasets that may reveal transfer limits and guide the design of a genuinely agnostic framework. The results will feed back into control-room tools at DESY and may be transferred to industry partners when appropriate (e.g., with Dataset 3).

Requirements:

  • Master's degree in mechatronics, electrical or control engineering, computer science, or related fields
  • strong programming skills in Python
  • experience in large-scale data handling and analysis and machine learning
  • knowledge in anomaly detection (machine learning) and fault diagnosis (control theory)
  • strong interdisciplinary research and team-work skills
  • interest in particle accelerators and physics
  • experience in industry or finances and the analysis of related data

Position:

  • Deutsches Elektronen-Synchrotron DESY
  • 75% EGR. 13 (TVöD) position for three years

At DESY, gender equality is an important aspect. To support work-life balance, we offer flexible working hours, variable part-time, job-sharing models, and participation in mobile work (up to 50%).

DESY promotes equal opportunities and diversity. The professional development of women is very important to us. Therefore, we strongly encourage women to apply for the vacant position.

Applications from severely disabled persons will be given preference if they are equally qualified (sbv.desy.de).

application-dashh@desy.de
Tel +49 (0)40 8998 2718

Open PhD Positions in Data Science

Application Deadline: October 31st, 2025

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Deutsches Elektronen-Synchrotron DESY

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Hamburg, Deutschland

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