Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Forschungszentrum Jülich
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung
- Deutsches Elektronen-Synchrotron DESY
- GFZ Helmholtz-Zentrum für Geoforschung
- University of Tübingen
- Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf
- Constructor University Bremen gGmbH
- FBN Dummerstorf
- Heidelberg University
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Helmholtz-Zentrum Hereon
- Leibniz
- Nature Careers
- University of Greifswald
- 6 more »
- « less
-
Field
-
Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 3 months ago
PhD in computer science, mathematics, physics, bio-/medical informatics or related fields, specializing in image analysis or machine learning, proficiency in deep learning techniques (CNN, VIT
-
Your Job: As part of an interdisciplinary project team with researchers from bioinformatics you will work on quantum algorithms for drug discovery. Here, the focus lies on machine learning and
-
practical experience in machine learning, especially deep learning and its practical application in the domain of language processing and sensor analysis Solid practical experience in the field of natural
-
coupled hydrological and groundwater modelling, combined with machine learning techniques, will quantify groundwater recharge and groundwater resilience. Your responsibilities: Analyse the dynamics
-
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
-
management skills • Experience with qualitative or mixed-methods research • Familiarity with AI, machine learning, neurotechnology, or robotics research contexts • Interest in science policy, governance
-
and others) Analysis of the experimental data, ideally connecting to our machine learning tools Presentation of scientific results on conferences and in publications Requirements PhD degree in physics
-
Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent academic record, including
-
-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
-
social or behavioral sciences (incl. human-computer interactions with relevant experience). Applicants must demonstrate experience in experimental work with human participants; possess versatile