Postdoctoral Researcher – Computational Electron Microscopy and Machine Learning

Forschungszentrum Jülich; Jülich; Vor Ort; EUR 60.000 - 75.000; Vollzeit

Benefits dieser Stelle

30 Urlaubstage

Flexible Arbeitszeitmodelle

Betriebliche Altersvorsorge

Internationale Forschungsumgebung

Kooperation mit ER-C

Zusammenfassung

Das Institut IAS-9 am Forschungszentrum Jülich sucht eine/n Postdoktoranden/in mit Schwerpunkt Elektronenmikroskopie und maschinellem Lernen. Sie entwickeln, trainieren und validieren Deep-Learning-Methoden für Mikroskopiedaten und arbeiten an realen Experiment- und Simulationsdatasets.

Sie publizieren in Mikroskopie- und Materialwissenschaftszeitschriften, ko-supervisieren Doktorandinnen und Doktoranden und arbeiten eng mit ER-C zusammen.

Qualifikationen

• Abgeschlossenes Master- bzw. PhD-Studium in Physik, Materialwissenschaft oder einem verwandten Fach.
• Fundierte Kenntnisse der Elektronenmikroskopie, Bildentstehung, Kontrastmechanismen sowie Erfahrung in mindestens einer der folgenden Techniken (4D-STEM, In‑Situ/Operando Mikroskopie, quantitative HR(S)TEM).
• Erfahrung mit Elektronenmikroskopie-Simulationen (z. B. Multislice, Bloch-Wave) oder mit Aufbau quantitativer Datenanalyse-Pipelines.
• Praktische Erfahrungen im Training von Deep-Learning-Modellen, Programmierkenntnisse in Python und Arbeitserfahrung mit PyTorch oder vergleichbarem Framework.
• Ausgeprägtes Interesse an Methodenentwicklung statt reiner Anwendungsforschung und Bereitschaft, ML-Kompetenzen im Team zu vertiefen.
• Ausgeprägte Kommunikationsfähigkeiten über Fachgrenzen hinweg; analytisches Denken und Kreativität.
• Sehr gute Englischkenntnisse in Wort und Schrift (mind. CEFR B2), idealerweise belegt durch Nachweis.

Aufgaben

• Forschungsschnittstelle zwischen Elektronenmikroskopie und Machine Learning, Anwendung bestehender Methoden und Dissemination der Ergebnisse.
• Identifizierung offener Fragestellungen in der Elektronenmikroskopie, die durch Analyse statt Instrumentierung limitiert sind.
• Entwicklung, Training und Evaluation von Deep-Learning-Modellen für Mikroskopiedaten (Realraum- imaging, 4D-STEM, In-Situ‑Datensätze).
• Festlegung, was physikalisch sinnvolles Evaluationsergebnis bedeutet und welche Fehlerarten relevant sind.
• Durchführung und Interpretation von Simulationsstudien (Multislice, Bloch-Wave) zur Verbindung von Experiment, Theorie und Modellverhalten.
• Zusammenarbeit mit ER-C, Veröffentlichung in Fachzeitschriften, Beitrag zu offenen Datensätzen und Software.
• Co- supervising von Doktoranden/Masterarbeiten und Mitwirkung an Drittmittelprojekten.

Kenntnisse

Elektronenmikroskopie-Kenntnisse

DL-Modelle anwenden

Python-Programmierung

PyTorch-Umgebung

Interdisziplinäre Kommunikation

Englische Sprachkenntnisse B2

Ausbildung

Master-Abschluss in Physik, Materialwissenschaft oder verwandtem Feld

PhD in Physik/Materialwissenschaft/Verwandtes

Tools

Multislice-Simulationen

Bloch-Wave-Methoden

Datenanalyse-Pipelines

Jobbeschreibung

The multidisciplinary Institute for Advanced Simulation - Materials Data Science and Informatics (IAS-9) brings together disciplines ranging from data analysis and machine learning to materials simulation, research data management and software development under one roof. In doing so, we extract new information from simulations and experiments, identify patterns and trends in microscopy data, and improve our understanding of why materials and processes work the way they do. We benefit from a strong connection to the Ernst Ruska-Centre for Microscopy and Spectroscopy with Electrons (ER-C) and to the Jülich Supercomputing Centre.

Within IAS-9, the Deep Learning for Electron Microscopy group develops machine learning methods grounded in the physics of the measurement rather than in generic image statistics. We are looking for a postdoctoral researcher whose scientific home is electron microscopy itself and who wants to develop the computational methods the field now needs: identifying where microscopy questions genuinely require new methods, developing them, and validating them against real experimental data.

Your Job

• Conducting research at the interface of electron microscopy and machine learning, including the application and adaptation of established methods, data analysis, and dissemination of results
• Identifying open questions in electron microscopy where progress is limited by analysis rather than by instrumentation, and where new machine learning methods therefore offer genuine scientific gain
• Developing, training and evaluating deep learning models for microscopy data – real-space imaging, 4D-STEM diffraction and in-situ time series – including the construction and characterisation of the experimental and simulated datasets your research requires
• Establishing what physically meaningful evaluation means for such models: what constitutes a correct answer, when an output is an artefact of the measurement, and which failure modes matter for the underlying materials science
• Conducting and interpreting simulation studies (e.g. multislice, Bloch-wave methods) that connect experiment, theory and model behaviour
• Participation in the scientific agenda of our collaboration with the ER-C: bringing microscopy questions into our method development, and turning model results into statements that are meaningful to microscopists
• Publishing in microscopy and materials science journals as well as at machine learning venues, and contributing to open datasets, benchmarks and software
• Co-supervising doctoral and master students, and contributing to proposal writing and to the group’s third-party funded projects

Your Profile

• Completed Master's degree and PhD in Physics, Materials Science or a closely related field
• In-depth working knowledge of electron microscopy, including image formation and contrast mechanisms, electron diffraction, and substantial experience in at least one of the following: 4D-STEM, in-situ or operando microscopy, or quantitative HR(S)TEM.
• Experience with electron microscopy simulations (e.g. multislice or Bloch-wave methods), or with developing quantitative data analysis pipelines for microscopy data, which would be a strong asset.
• Practical, hands‑on experience in training deep learning models, solid programming skills in Python, and working proficiency with PyTorch or an equivalent framework.
• A clear interest in developing methods rather than merely applying them, as well as the motivation to substantially deepen your machine learning expertise within the group.
• Excellent communication skills across disciplinary boundaries; much of the value of this role lies in enabling two research communities to understand one another.
• Strong analytical skills, creativity
• Very good command of written and spoken English with extensive vocabulary is required (at least B2 level according to the CEFR

), ideally supported by a certificate confirming the language level

Our Benefits for You

We work on highly topical, socially relevant issues and offer you the opportunity to actively shape change! You can expect a wide range of opportunities:

• Meaningful tasks: The opportunity to conduct exciting research in an international and multidisciplinary environment with outstanding infrastructure and to strengthen your reputation in a dynamic and highly active research field
• Work Environment: A creative work environment at a leading research facility, located on an attractive research campus at the TZA Aachen and the Forschungszentrum Jülich

and the Forschungszentrum Jülich

• Work Location: The work location may vary between Aachen and Jülich. Initially, the work will primarily take place in Aachen
• Scientific Exchange: The opportunity to attend national and international conferences
• Work-life balance: Optimal conditions for balancing work and private life, as well as a family-friendly company policy. The option of flexible working (in terms of location) is generally available after consultation and in line with upcoming tasks and (on-site) appointments
• Vacation: You will receive 30 days of vacation plus additional days off (e.g. between Christmas and New Year's)
• Flexibility: Flexible working time models, including options close to full‑time

allow you to tailor your working hours to suit your individual needs

• Knowledge & further training: Your professional development is important to us – we provide targeted, individual support
• Health & well‑being: Your health is important to us. You can look forward to a comprehensive occupational health management program with a wide range of offerings - e.g., a beach volleyball court, running groups, yoga classes, and much more. In addition, our company medical service and an experienced social counseling team are available to assist you on site
• Successful start: It is important to us that you quickly settle into the team and are given structured training for your tasks. We also support you from the very beginning and make your start easier with our Welcome Days and Welcome Guide
• Fair remuneration: Depending on your existing qualifications and the tasks assigned to you, you will be classified in pay grade 13 of the TVöD-Bund (Collective Agreement for the Public Service). All information on the TVöD-Bund collective agreement can be found on theBMI website
• The monthly salaries in euros can be found on page 69 ff. of the PDF download
• Additional benefits: Benefit from attractive additional services such as a company pension scheme with employer contribution. In addition to the basic salary, there is an additional year‑end bonus under the collective pay agreement amounting to 75% of a monthly salary, as well as capital‑forming benefits
• Perspective: After a 2‑year fixed‑term contract, our goal is to hire you on a permanent basis. Let's use this time to find out how well we fit together or
• Support for international employees: Our International Advisory Service makes it easier for international employees to get started
• Career Center: You will receive explicit support with regard to your career development opportunities

In addition to exciting tasks and a collegial working environment, we offer you much more:

https://go.fzj.de/benefits

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.

The following links provide further information on diversity and equal opportunities:

https://go.fzj.de/equality

and on specific support options for women: https://go.fzj.de/womens-job-journey

• Place of Employment:**Aachen und Jülich

Start Date: As soon as possible

Working Hours: 39 Hours / Week

Salary: Pay group 13 TVöD-Bund

Application Deadline: The position will be published until it is successfully filled

Index number: 2026T-0645