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computational methods and algorithms for genomic sequencing data analysis, particularly in the context of genome assembly. This is an exciting opportunity to develop novel computational approaches for microbial
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programming and algorithm development, with proficiency in Python, Perl, C/C++, or Java, and statistical computing using R Demonstrated experience in designing, training, validating, and deploying machine
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models to specialized microscopy tasks and develop algorithms that align image level embeddings across modalities (e.g., fluorescence ↔ electron microscopy ↔ brightfield ↔ …). In collaboration with other
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physics, materials science, chemistry and related fields. The development of the concepts, algorithms and code libraries needed to advance the field is fundamental to the work of the center. Research
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incorporate modern genomic and biochemical approaches to resolve questions such as 1) how developmental pathways are altered by evolutionary processes, leading to new structures and features, 2) how intricate
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management. Demonstrated experience in one or more applied computational fields: application of modern machine learning methodology, algorithms, computational modeling, finite element analysis, computational
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techniques and the structure of bilevel problems in large-scale settings. Objectives The goal of this postdoctoral project is to develop scalable blackbox optimization algorithms tailored to bilevel problems
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technologies, software development, algorithm design, and data applications. Discipline, including, but not limited to: Computer Science and Technology, Cyberspace Security, Data Science and Big Data Technology
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multiphoton calcium imaging data Registration and integration of spatial transcriptomics and in vivo imaging data Optimise and maintain data analysis pipelines Refine algorithms for image registration, cell
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, Zarr). Familiarity with state of the art (self-supervised) computer vision algorithms (e.g., DINO, Masked Autoencoders, SAM). Experience with ML model deployment, workflow orchestration, and high