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Field
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, and therapy resistance mechanisms Ability to work independently and collaboratively within interdisciplinary teams Prior experience with network modeling or machine learning is a plus We offer
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novel biomarkers by integrating proteomics, metabolomics, and genomics / transcriptomics data with machine learning techniques. The position is to be filled starting November 1, 2025, either full-time or
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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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and machine learning to establish a modeling framework that uses omic data for providing effective degradation rates of biomolecules and predictions of their impact on soil organic matter turnover
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 20 days ago
. Helmut Grubmüller) is inviting applications for a PhD Student or Postdoc (f/m/d) for the project Theory and algorithms for structure determination from single molecule x-ray scattering images. Project
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. Specifically, the PhD candidate is expected to contribute corpora preparation (collection and organizing the annotation), use machine learning approaches for irony detection, and testing for experimental and
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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Senior Scientist / Group Leader on Bioinformatics / Computational Biology on RNA Regulation in Disea
studies Apply machine learning to uncover novel mechanisms and therapeutic insights Mentor junior scientists, contribute to grant writing and publications, and drive the lab’s scientific vision Apply
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training