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learning models (e.g., PCA, PLS-DA, clustering, CNNs) to classify microplastic particles based on spectral and morphological fluorescence data. Develop and maintain modular analysis pipelines in Python
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Education: PhD in Artificial Intelligence, Bioinformatics, Computer Science, Physics, Engineering, or a related field. Programming: Proficient in Python. Machine Learning: Strong experience with frameworks
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, ability to critically discuss and present scientific results, and proficiency in English for oral and written communications. Experience with genome editing, bioinformatics (e.g. python, linux) and high
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(Python-friendly) A collaborative, supportive mindset and motivation for clinically relevant science Bonus but not required Experience with cryo-FIB milling/lamella preparation Experience
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biology, bioinformatics, genomics, statistics, physics, or a related quantitative field Demonstrated ability to analyse large-scale sequencing data using R, Python or equivalent A self-motivated team player
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: Proficient in Python. Machine Learning: Strong experience with frameworks like TensorFlow, Keras, or PyTorch. Preferred Skills: Experience with Explainable AI (e.g., SHAP, Integrated Gradients
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biology, bioinformatics, genomics, statistics, physics, or a related quantitative field Demonstrated ability to analyse large-scale sequencing data using R, Python or equivalent A self-motivated team player
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biomedical or engineering sciences and a strong affinity with movement and rehabilitation sciences. You are proficient in programming in Matlab and, if possible, Python. You have experience in using 3D motion
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representation learning. You have strong programming skills, especially in Python, and preferably experience with PyTorch. You have a track record of publishing in top image processing / computer vision journals
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strong background in shape modelling, deep generative modelling (diffusion/transformers), or multimodal representation learning. You have strong programming skills, especially in Python, and preferably