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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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-world buildings, data analysis, and modeling. Candidates with complementary expertise who are interested in developing new research directions within the broader field of indoor air quality are also
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, No UMO-2020/39/I/NZ5/03104, Dissecting cancer activome to develop new generation of antibody-drug conjugates, PI: PhD. Eng. DSc. Marcin Poręba, professor at WUST Type of position: research assistant
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the development of therapeutic strategies to promote neurological recovery. The successful candidate will use a combination of in vivo and in vitro approaches, including animal models, molecular and
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candidate’s interests and expertise. Our lab investigates a broad range of questions related to the origins and molecular evolution of organs in mammals and other vertebrates and the underlying genomic changes
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knowledge of data analysis and processing, programming, and development of analytical models. Experience with databases and quantitative analysis tools. Ability to work with large datasets and computational
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Post Doctoral Researcher / Senior Post Doctoral Researcher - School of Biochemistry and Cell Biology
period of training as the researcher will have dual goals in terms of the research project and their own career development. The researcher will be mentored by a Principal Investigator (PI). It is expected
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Post Doctoral Researcher / Senior Post Doctoral Researcher - School of Biochemistry and Cell Biology
researcher will have dual goals in terms of the research project and their own career development. The researcher will be mentored by a Principal Investigator (PI). It is expected that a researcher would spend
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. This postdoctoral focuses on developing a new paradigm for the circular manufacturing of heterogeneous photonic integrated circuits. While heterogeneous integration has emerged as the leading approach for combining
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The ultimate objective of this project is to detect cognitive strategies in single-trial EEG data. In very broad terms, we will use the HMP method (https://github.com/GWeindel/hmp ) to discover