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), immunofluorescence and microscopy Prior experience in RNA biology, NGS and/or Metabolism is an asset Understanding of common bioinformatics approaches and experience with one of the main programming languages for data
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. For more information, please visit our website: www.uni.lu/snt-en/research-groups/finatrax/ The selected candidate will be enrolled in the PhD program in Computer Science and Computer Engineering with
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The position is funded for 3 years (65% TV-L E13), starting on January 1st, 2026, within the framework of the TTU HIV program of the German Center for Infection Research (DZIF). Project Description: Although
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science or related discipline Experience and skills Experience in developing MLIPs, including good programming skills in Python and C, demonstrated via contributions to code repositories Experience with
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computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline Knowledge and experience in the analysis of metagenomics and/or biological high-throughput
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
. Responsibilities and qualifications Your overall focus will be to establish and lead a strong research program in the field of synthetic biology and metabolic engineering of non-model microorganisms, with the aim
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curiosity, innovation and entrepreneurship in all areas Personalized learning programme to foster our staff’s soft and technical skills Multicultural and international work environment with more than 50
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of programming languages. The ideal candidate has an MSc in Computer Science or Mathematics and experience in one or more of the following areas: Theory of programming languages. Logical methods in
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, including participation in coursework, journal clubs, and training events Your Profile Master’s degree (or equivalent) in neuroscience, biology, or a related discipline Proficiency in English (spoken and
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programme at the Faculty of Science . The ideal candidate has a background in or experience with one or more of the following topics: SIMD performance engineering. Machine Learning. Communication-efficient