Sort by
Refine Your Search
-
Employer
- Technical University of Munich
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V.
- Deutsches Elektronen-Synchrotron DESY •
- Fraunhofer-Gesellschaft
- Hannover Medical School •
- Karlsruhe Institute of Technology •
- Ludwig-Maximilians-Universität München •
- Max Planck Institute for Biological Cybernetics, Tübingen
- Max Planck Institute for Sustainable Materials •
- Saarland University
- Technische Universität München
- University of Hamburg •
- 3 more »
- « less
-
Field
-
-cell imaging, multi-omics profiling such as transcriptomics, proteomics, and metabolomics, single-cell and spatial analyses, multiplex biomarker quantification, functional studies, machine learning
-
FieldComputer scienceEducation LevelMaster Degree or equivalent Skills/Qualifications Strong foundations in Machine Learning and Deep Learning Excellent Python programming skills Experience with PyTorch
-
data • Design clinically meaningful benchmarks and robust evaluations • Publish at leading machine learning and medical AI venues • Collaborate with clinicians, computer scientists, and European partners
-
–2 years, total 3–4 years) on deep learning for medical imaging. This DFG-funded project focuses on developing deep learning methods for medical and scientific imaging. The Professorship for Machine
-
or complementing traditional physics-based approaches by data-driven ones, using Machine-Learning (ML). Such approaches allow enormous gains of time, in a way that can be related to the astonishing efficiency
-
programming skills in Python; initial experience with machine learning frameworks such as PyTorch or TensorFlow Initial practical experience from a master's thesis, study projects, internships, or open-source
-
imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
-
Course location Hamburg Description/content The Cluster of Excellence "CUI: Advanced Imaging of Matter", funded by the German federal and state governments, combines projects in physics, chemistry
-
mechanisms occurring in these materials and their synthesis over all relevant length scales (e.g., cutting-edge ab initio methods, atomistic simulation methods, multi-scale modelling, machine learning) High
-
important roles: data management and engineering, machine learning and data analytics, signal and image processing, algorithm design, optimisation and simulation, software engineering and automation and