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, that combines diffusion and transformer models, there are clear indications that the analysis of this data can be automated. This will open new avenues in data interpretation and building predictive models
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at the cellular level, and (iii) applying quantitative image analysis to compare structural organization across fertile and infertile donors. The project is embedded in an active collaboration with a local
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neurodevelopmental conditions, by bridging disciplines, from artificial intelligence, microelectronics, neuroengineering and nanoscience, to single-cell, imaging and molecular analysis, functional genomics and cell
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). The position is available upon agreement. For further information visit https://brunnerlab.sites.vib.b... and contact Prof. Janine Brunner (janine.brunner@vub.be).
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past successes: https://europepmc.org/article/MED/35021063 , https://europepmc.org/article/MED/31819264 , https://europepmc.org/article/MED/31561945 , https://europepmc.org/article/MED/39747019 , https
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with large-scale data analysis, such as genomics or transcriptomics data Experience with a workflow management system such as Snakemake or Nextflow A willingness to learn and apply machine learning
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(Python, MATLAB) for behavioral data analysis Preferred Qualifications: Experience with rodent behavior assays Familiarity with tools like DeepLabCut, MoSeq, or Kinect-based systems Interest
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will include data acquisition, analysis, and interpretation, as well as collaboration with clinicians for human tissue studies. The candidate holds a Master degree in biomedical sciences, medicine