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-generation sequencing and single-cell technologies (e.g., scRNA-seq, scATAC-seq, scTR-seq, and/or spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable
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-based spatial transcriptomics are preferred. Candidates with at least 2 years experience in generating and analyzing single-cell RNA-Seq data from both primary retinal tissue and retinal organoids
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, viability and biological function. The work will require rigorous experimental design, appropriate controls and benchmarks, statistical analysis, traceable data and predefined acceptance criteria. The role
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, Spatial data analysis or GIS Whole-genome sequencing, phylogenetics, or phylodynamics Data management and reproducible analytical workflows Quantitative modeling and statistical inference. Applicants
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Engine. Knowledge of experimental design, spatial statistics, and yield data processing workflows. The Successful Candidate Will Demonstrate excellent organizational skills and the ability to manage
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or Computer Science; Human-computer Interaction, Spatial Cognition or related areas; Engineering, Applied Mathematics, Statistics or another Quantitatively Oriented Discipline. Application procedure Your complete
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in computational methods and/or quantitative methods, primarily spatial analysis. Experience in supervising and managing research groups. Experience in conducting academic research related to analyzing
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or R. Experience working in a Linux environment and using command-line tools. Knowledge of statistical methods and the ability to apply them to biological data analysis. Experience in the analysis
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Department of Spatial Economics The Econometrics and Data Science department aims at pushing the academic frontier in methodology development for quantitative, statistical modeling of data, ranging
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combines stem cell biology, spatial genomics, AI/ML, single-cell technologies and computational biology to study how mutant cell populations interact with their surrounding tissue environment during