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reference frames, transformations, international connections, geoid modelling and metrology. Website for additional job details https://valtiolle.fi/en/jobs/phd-student-postdoc-15184/ Work Location(s) Number
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, when relevant; Contributing to university courses offered by the department. Your qualities Required qualifications: A PhD in ecology, plant sciences, environmental sciences, or a closely related field
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imagery). Experience in building data models using Python or other statistical and/or mathematical programming packages. Proficiency in developing machine learning algorithms to analyze spatial-temporal
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cancer progression, immune evasion, and therapeutic resistance. We place a strong emphasis on the use of spatial biological approaches applied to human tumour models including organ/tumour perfusion, slice
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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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. The position will be available for a 3-year period. You will be part of a research environment focusing on applying digital solutions to map spatial and temporal variability of crop growth as well as evaluate
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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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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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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, Nature Energy 2024] to image operating perovskite solar PV cells with high spatial (hundreds of nanometers) and temporal (hundreds of picoseconds) resolution. This project will push these capabilities