Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Technical University of Munich
- Nature Careers
- Forschungszentrum Jülich
- Heidelberg University
- Leibniz
- Karlsruher Institut für Technologie (KIT)
- Catholic University Eichstaett-Ingolstadt
- Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt
- Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association
- Max Planck Institute for Evolutionary Anthropology, Leipzig
- Max Planck Institute for Mathematics in the Sciences
- Max Planck Institute for Molecular Genetics, Berlin
- Max Planck Institute for Multidisciplinary Sciences, Göttingen
- Max Planck Institute for Solid State Research, Stuttgart
- TU Dresden
- Technische Universität Ilmenau
- University of Tübingen
- Universität Freiburg, Historisches Seminar
- 8 more »
- « less
-
Field
-
or spatial transcriptomics. Strong programming (Python / R) and analytical skills, with proficiency in bioinformatics tools, statistics and machine learning. A creative and problem-solving mindset, capable
-
Computer Science with a mathematical emphasis, or in a related field, by the time of employment. Profound knowledge in data assimilation—particularly in particle filtering—as well as in data science, machine
-
or application of machine learning/optimization methods Have good English communication skills An exceptional candidate may optionally have one or more of the following experiences: Experience in analyzing spatial
-
for reward funds such as voluntary carbon markets, offset markets, or tax clubs (e.g. on aviation, maritime shipping, or luxury goods). Use of empirical or machine-learning techniques for estimating baseline
-
success rates of real, patient-specific aneurysms, their treatment options, and long-term prognosis. The project is complemented by contributions in machine learning, such as the rapid generation
-
motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
-
colon. The project is funded through the ERC "Unstable Genome". The position is co-supervised by Wolfgang Huber at EMBL and Dr. Aurélie Ernst at DKFZ. The Huber group develops statistical and machine
-
areas, notably in Physics-Enhanced Machine Learning, Computer Vision & AI, and AI in Health Care and Medicine.The position is a full-time position (100%), initially for 2 years and 3 months, with
-
biophysics, computational biology, mathematics in the life sciences, computer science and machine learning with application to biological systems, and related areas. What we provide The CSBD provides fully
-
moderation can be exploited by malicious actors to circumvent controls. The research will involve leveraging insights from machine learning on strategic classification and conducting lab experiments to assess