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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
, or pediatric diseases (prior experience is an advantage but not required) Experience with or willingness to learn biomarker analyses (e.g. ELISA), histological techniques, and molecular assays Interest in animal
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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves
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experience Academic Diplomas (MSc/PhD) You can learn more about the recruitment process here . Please indicate whether you are applying for the position as a Senior Researcher or Researcher. Applications
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biomedical research. Your profile Master's degree in computer science or related discipline Experience with Python and recent deep learning frameworks (e.g. Pytorch, MONAI) Strong interest in image analysis
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assessment of chemical plants using HAZOP analysis Use of process modeling and simulation to enhance quantitative assessments Use of machine learning to support HAZOP discussions with the aim of obtaining a
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learning and modelling to reveal plant-soil-microbe interactions. Your findings will inform climate and environmental policy and may contribute to shaping Australia’s carbon credit system. You’ll work with a
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PhD student (m/f/d) in the field of chemistry, chemical engineering, materials science or comparable
polyoxometalates Using suitable characterization methods to characterize the synthesized materials Using machine learning tools to tune the synthesis parameters in a feedback loop and enhance the properties
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Human-centric Digital twins for monitoring robotized biostimulants application practices. University Milan (IT) & Université Libre Bruxelles (BE) Position E Optimizing Images Quality and Deep Learning
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for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion phenomena and link speciation with
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, etc.), and data-driven methods (optimisation, generative AI, agent-based modelling, machine learning). Our work provides decision support for policy makers, industry stakeholders, and researchers by