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causal networks that govern cellular behavior from large-scale single-cell datasets. Our group has pioneered computational approaches for: Inferring causal networks from Perturb-seq (interventional single
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influenced corrosion (MIC) in marine environments. It uses AI-supported models, Bayesian data fusion, and real-time sensor data integration. Your responsibilities include: Development of a digital twin (DT
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for inferring signatures of natural selection. The position is supposed to be filled at the earliest possible date and initially funded for 2 years with the possibility for extension. Compensation with all public
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algorithms, NLP models, and LLMs to analyze complex data. Designs and implements novel data science methodologies for predictive modeling, causal inference, and probabilistic analysis in clinical and
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across disciplines. Desirable: Experience in explainable AI, causal inference or autonomous systems Publications in AI, genomics, single-cell or precision medicine Background in rare disease, cancer
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. The goal is to build foundation models capable of learning from richly structured or semi-structured data where traditional graph neural networks may fall short, enabling better representation, inference
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Network Inference https://www.umu.se/en/ucmr/ec-postdoc-programme/ncrna_net-development-of-a-novel-approach-to-lncrna-mrna-regulatory-network-inference/ 7. Virome–vector competence shifts: How mosquito
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, for discovery, prediction and causal inference in epidemiological studies (including but not limited to genome-wide association studies of molecular phenotypes, Mendelian Randomization, co-localisation
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phenotypes coupled with genotypes, for discovery, prediction and causal inference in epidemiological studies (including but not limited to genome-wide association studies of molecular phenotypes, Mendelian