Fully-funded PhD position fully-funded under the CSC 2021
⛔️ Valid only for Chinese students
👩👨Supervisors: Prof. Ribana Roscher (University of Bonn) and Dr. Gabriele Cavallaro (Jülich Supercomputing Centre)
⌚️Starting date: September 2021
🌡(Due to the current corona pandemic, the first work period can be conducted remotely)
🌍Location: Jülich (Germany). You will be employed at the Jülich Supercomputing Centre and enrolled as a PhD student at the University of Bonn.
🔬Goal: research of advanced deep learning methods with modular supercomputing architectures in applications from remote sensing.
👨 👩 👴 👵 🧔Research Group: be part of our research group “High Productivity Data Processing" which is highly active in developing parallel and scalable machine (deep) learning algorithms for remote sensing data processing and many other types of applications (i.e., medical research and retail sectors).
⚒Working Environment: Direct access to high performance multi-GPU systems equipped with the state-of-the-art of DL frameworks (TensorFlow, pyTorch, Chainer, Horovod, DeepSpeed). There is also the possibility to access innovative quantum computing systems.
📝Other information: You will have the possibility to participate in international top conferences in the field of machine learning, HPC and remote sensing. You will be put in contact with several international partners for initiating research collaborations that match the topic of the PhD.
📓 Background education: MSc degree in computer science or computer engineering. Level of English >= B2.
🧠Required knowledge and experience: deep learning (Convolutional Neural Networks and/or Transformers) and Python programming (TensorFlow and/or pyTorch). Experience with parallel programming (OpenMP and MPI), High Performance Computing (HPC) and remote sensing data processing are a substantial plus.
👉Apply: Send your CV, a cover letter and the transcripts of records of your bachelor and master to Gabriele Cavallaro (firstname.lastname@example.org)