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Professor (25260446) Responsibilities: The Department is recruiting one scholar at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics
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on: https://www.dges.gov.pt/pt/pagina/reconhecimento Workplan and the objectives to achieve: The workplan proposed comprises two topics, each to be tackled by each studentship offered: Topic 1 - Automatic
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we use include standard cell and molecular biology techniques, flow cytometry, microscopy (standard imaging and FRET, FLIM, FRAP), high throughput genetic and chemical screens, single cell and spatial
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of Bioinformatics. • Experience in Genomic studies. Functions • Multi-omics data analysis. • Single-cell data analysis. • Spatial biology data analysis. Predoctoral contract. • Reference: PREP2024-002764 • Annual
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associate to carry out research on machine spatial reasoning. The appointment is for one year, renewable for a second year, given the availability of funds. The focus is on developing tools for characterizing
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI SCIENZE BIOLOGICHE, GEOLOGICHE E AMBIENTALI | Italy | 3 months ago
Description This project enhances Earth observation data cubes by improving two key processes: image coregistration and fuzzy classification. Accurate data cubes require precise spatial alignment and reliable
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methods for forensics, life sciences, topological data analysis, spatial statistics, and computational statistics). The department values an informal atmosphere with strong collegial support, openness, and
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spatial, temporal, or spatiotemporal modeling, process-informed spatiotemporal models, causal inference, AI/ML/DL, causal ML, explainable ML, AI/ML/DL, and other relevant analytical skills. Experience
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between connecting and dividing dynamics in contemporary processes of historical globalisation. Its collective work centres around researching how spatial, social, political, cultural and ethnic differences
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beyond descriptive genomics to decipher the underlying regulatory logic of GBM. By leveraging single-cell multi-omics (scATAC-seq, scRNA-seq) and spatial omics, you will map enhancer landscapes