PhD position – Deep Learning for Dislocation Analysis in Electron Microscopy

Overview

PhD position – Deep Learning for Dislocation Analysis in Electron Microscopy at Forschungszentrum Jülich. The PhD project is methodologically independent, with the opportunity to contribute to collaborative efforts at the interface of data science, imaging, and materials research. You will strengthen the data science and machine learning activities of the IAS-9 with exciting new topics in a multidisciplinary team of data scientists, software developers and domain scientists.

Responsibilities

• Developing self-supervised learning frameworks to extract features from unlabeled high-resolution microscopy data
• Training and evaluating segmentation models for detecting and characterizing defects such as dislocations
• Applying generative models (e.g., GANs, diffusion models) to augment microscopy datasets
• Investigating domain adaptation techniques across different imaging modalities
• Collaborating closely with experimental partners to validate methods and integrate tools into existing workflows
• Disseminating findings through scientific publications, international conferences, and open-source contributions

Profile / Qualifications

• A completed university degree (Master or equivalent) in computer science, data science, applied mathematics, physics, materials science, or a related field
• Prior experience in computer vision, deep learning, or signal processing; familiarity with microscopy data is an asset but not required
• Interest in foundational machine learning research with applied impact in scientific imaging
• Proficiency in Python and experience with ML/DL frameworks like PyTorch or TensorFlow
• Strong analytical and communication skills, creativity, and the ability to work independently while collaborating in a team-oriented environment

We Offer

• A dynamic, interdisciplinary research environment at the forefront of materials informatics
• Comprehensive training courses and individual opportunities for personal and professional development, including JuDocS and the Jülich Center for Doctoral Researchers
• Opportunity to attend national and international conferences
• Optimal conditions for work-life balance, including family-friendly policies, flexible working hours, the option for home office days, and 30 vacation days per year
• A creative work environment at a leading research facility, located on the Forschungszentrum Jülich campus in Jülich/Aachen
• Flexible working hours in a full-time position with the option of slightly reduced working hours
• Targeted services for international employees

Neben spannenden Aufgaben und einem kollegialen Miteinander bieten wir Ihnen noch viel mehr:

Location and Term

Place of employment: Jülich/Aachen. The position is for a fixed term of 3 years.

Compensation

Pay in line with 75% of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund) and additionally 60% of a monthly salary as special payment. Pay higher than the basic pay may be possible. Salaries are published on the BMI website:

Application

We are looking forward to your application including a CV, university degree certificates, grade transcripts, two references and/or letters of recommendation, and a motivation letter. Please highlight relevant experience in your motivation letter.

We welcome applications from people with diverse backgrounds and are committed to equal opportunities in a diverse and inclusive working environment. Further information on diversity and equal opportunities:

Seniority level

• Internship

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Research

Place to set job alerts: Aachen, North Rhine-Westphalia, Germany

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