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Software Engineer - Image Quantification and Artificial Intelligence (IQAI), Department of Radiology
, and ensure reproducibility. Build user-friendly interfaces and APIs that enable radiologists and researchers to interact with complex image analysis algorithms. Translate computer vision and deep
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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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the project's personalized treatment algorithms. For further information, please contact Prof. Dr. Antonio del Sol, antonio.delsol [at] uni.lu . Your profile Ph.D. degree in computational biology, bioinformatics
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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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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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. Experience with phase retrieval algorithms, clean room use and e-beam lithography are beneficial. The candidate will be expected to participate at international user facilities and thus will be expected
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://www.hogberglab.net/ ). You will contribute to the ERC Advanced Grant project qScope , where you will create and improve existing bioinformatic tools and network algorithms to help us to map RNA or protein molecules in
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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental