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research team. Our work focuses on craniofacial regeneration and distraction osteogenesis, using cutting-edge multi-omic approaches (single-cell and spatial transcriptomics, genetic and biochemical analysis
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part of our team, you will leverage state-of-the-art single-cell, spatial and organoid technologies in a collaborative and interdisciplinary environment. Research focus We welcome candidates with a
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, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific literature). Our
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practices ● Fluency in programming languages such as R and Python. ● Demonstrated ability to make reproducible code for cleaning, integrating, and modeling spatial/temporal data from multiple sources, spatial
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October 2025 Apply now The Department of Earth Sciences is looking for a highly motivated postdoctoral candidate with a background in numerical modeling (DEM, FEM, BEM). Your job You will work on the
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postdoctoral and PhD researchers on the team*Interest in developing and applying Large Language Models (LLM) and spatial Machine Learning (ML) modelsSalary and full employee benefits are offered in accordance
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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tools, data science techniques, and spatial analysis to leverage big data from cities and model their evolution. Main Tasks and Responsibilities: Collect, clean, and structure large volumes of urban
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. Specifically, the project will: Address a fundamental knowledge gap about how chromatin 3D organization determines transcription at a global scale in an explicitly defined neuronal development model. Integrate
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‐based visualization and user-interaction interfaces, including 3D modelling, physics integration, and cross-platform deployment (PC, mobile, AR); integrating and deploying AR navigation applications