Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Nature Careers
- Leibniz
- Technical University of Munich
- Forschungszentrum Jülich
- Heidelberg University
- Max Planck Institute for Dynamics and Self-Organization, Göttingen
- Max Planck Institute for Plasma Physics (Greifswald), Greifswald
- University of Tübingen
- Fritz Haber Institute of the Max Planck Society, Berlin
- Max Planck Institute for Astronomy, Heidelberg
- Max Planck Institute for Human Development, Berlin
- 1 more »
- « less
-
Field
-
science, automation science, or a related field, and convincing expertise in robotic hardware. Experience with machine learning and large language models is highly desirable. Prior experience in a biological setting
-
ability to quantify and model these processes remains limited, contributing to uncertainties in global carbon sink estimates. You will analyze data and samples from past and upcoming expeditions to evaluate
-
integrate large-scale sequence and RNA-seq data from internal and public resources. You build a reference library of predictive regulatory motifs. You use network analysis and random-forest approaches
-
-08187-1 Your Profile: Master and PhD in biology, genomics or bioinformatics Strong background in data science or machine learning (deep learning, statistical modeling, or large-scale data analysis a plus
-
countries. We also host a large data set of > 30,000 terrestrial insect species, based on DNA metabarcoding. Additionally, we have access to accompanying environmental data. These data sets provide a unique
-
European sea basins over decadal timescales, due to coastal darkening (COD) and artificial light at night (ALAN), and will determine drivers, sources and impacts of these changes at both large and small
-
at large scale facilities Establishment of cooperation projects with energy-related institutes at Forschungszentrum Jülich Initiating grant applications Supervision of MSc and BSc students Presentation
-
working with ocean or earth system models, or similar models A background in analyzing large data sets and visualizing data using Python, MATLAB, or equivalent very good writing, presentation, and
-
journal articles Contribution to the overall support of the project, working group, and team collaboration Requirements: PhD in data science, or in any field with relevant experience Experience with
-
us We are TUM’s unique Pathology AI lab developing new machine learning (ML) methods for automatically analyzing digital pathology data and related medical data. Such methods include the automatic