Phd-position - Data Mining, Inference, Prediction

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, structure, and trends in microscopy data, and ultimately improve our understanding of why materials, processes, or general systems work the way they do. To do this, we use a wide range of different methods, from classical statistical analysis through machine learning to method of artificial intelligence. One focus of our research activity is on data mining and high-throughput/on-the-fly analysis of microscopy data, but we are equally enthusiastic when it comes to other data, for example for extending classical simulations with data-based models. In many cases, "injecting" scientific domain knowledge into machine learning models is an important amplifier for the models we develop. **Your Job**: You will strengthen the data science and machine learning activities of the IAS-9 with exciting new topics. You will work in a multidisciplinary team of enthusiastic data scientists, software developers and domain scientists on, e.g., - Development and adaption of existing data mining and machine learning models - Design and implementation of machine learning algorithm for extracting information from experiment data - Evaluation and development of specialized and/or interpretable machine learning approaches for the domain of materials science, physics, microscopy - Incorporation of machine learning results with simulation methods - Working on project-related tasks where you can interact with other scientists, and collaborate with project partners - Preparation of scientific publications and participation in international conferences and workshops **Your Profile**: We are looking for a highly motivated colleague who is excited about new scientific endeavors with interdisciplinary approaches. For this you have: - Practical experience in the area of data analysis, data mining and ML/DL demonstrated through, e.g., a thesis, publications in peer-reviewed journals or open source projects - Strong programming skills in python and experience with deep learning frameworks (e.g., pytorch,) - Prior knowledge and experience with microscopy, topography or crystallographic defects is highly desirable - Prior knowledge and experience with FEM software (e.g. FENICS,) is highly desirable - Structured and analytical thinking as well as a systematic, careful, independent, and reliable working method - Excellent communication skills and commitment to work as part of a team **Our Offer**: We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change We offer ideal conditions for you to complete your doctoral degree: - The opportunity to conduct exciting research in an international and multidisciplinary environment with outstanding infrastructure - The opportunity to attend national and international conferences - Extensive company health management - Ideal conditions for balancing work and private life, as well as a family-friendly corporate policy - Flexible working hours, the option of slightly reduced working hours - Continuous mentoring from your scientific supervisor - 30 days of annual leave and provision for days off between public holidays and weekends (e.g. between Christmas and New Year) - Place of employment: Jülich/Aachen