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integration of heterogeneous data sources. Experience with signal processing and statistical modeling of high-dimensional data. Strong programming skills in Python and relevant ML frameworks (PyTorch
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decision is made. Strong experience in deep generative models (e.g., diffusion models, VAEs, transformers) Programming proficiency in Python and PyTorch Interest in multimodal human communication and virtual
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working with large data sets. Strong programming skills (e.g. Python, PyTorch) Ability to work both independently and collaboratively in a multidisciplinary team. Preferred qualifications A doctoral degree
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ability to handle large and complex datasets, including preprocessing and integration. Strong programming skills (e.g., Python, R, MATLAB, or similar). Demonstrated ability to conduct independent research
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(e.g., in MATLAB or Python) Strong publication record in leading Q1 journals and top-tier international conferences Excellent communication and presentation skills in English Independent, curious, and
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. The candidate is expected to have a solid grounding in programming in R, Python, and mathematics/statistics. The main duties involved in a post-doctoral position is to conduct research. Teaching may
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Optimal Control Theory Strong programming skills in C++/Python/MATLAB Familiarity with parallelization and high performance computing (CPU and GPU friendly code) Experience with Machine Learning, generative
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in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings
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ability to comfortable processing these data using tools like Seurat, Scanpy, or QuPath. Proficiency in Python or R, coupled with familiarity with machinelearning frameworks (e.g., scikit‑learn, PyTorch
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite