51 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" positions at Forschungszentrum Jülich
Sort by
Refine Your Search
-
Category
-
Program
-
Field
-
neuroscience is essential Experience with modelling, analysis of complex dynamical systems, simulation, analysis of large-scale datasets with machine learning methods, and software development are beneficial
-
sound understanding of data evaluation Prior experience with single-cell data analysis, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently
-
the collected data in accordance with FAIR standards for collaborative use within the Decode project and for machine learning applications Presentation of results in team meetings and preparation of a
-
skills (Python, R, Java, …) and interest to work in polyglot software environments Practical experience with machine learning and AI methods and an interest to learn, adapt and apply ML methods
-
Your Job: Modeling and characterization at molecular level of selected biological processes by performing classical molecular dynamics, and employing enhanced sampling methods and machine learning
-
twin of sperm motility, and utilize it to develop a separation method. Your tasks will include: Performing computer simulations and matching them to experimental data Very close collaboration with
-
Your Job: Research and extract industrial and commercial buildings across Germany using open-source geospatial data (e.g. OpenStreetMap, CORINE Land Cover, Sentinel, etc) Apply machine learning/AI
-
Your Job: In this position, you will be an active member of our Simulation and Data Lab for AI and Machine Learning in Remote Sensing, which aims to strengthen interdisciplinary research and
-
and sensor data processing, bioinformatics, systems biology, or biophysics. Familiarity with simulation environments, numerical methods, or machine learning approaches is an advantage. Fluent command
-
results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based