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- MASARYK UNIVERSITY
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Field
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-generation carriers. A major limitation remains the incomplete understanding of nanoparticle assembly and disassembly under diverse physiological conditions (e.g., extracellular fluids, endosomal compartments
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(fzu.cz ). What you will do Investigate and optimize the epitaxial growth of complex semiconductor heterostructures while incorporating dilute magnetic semiconductors and altermagnetic materials Combine
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and Phylogenetics Employment relationship: Employment contract Job type: Researcher Researcher profile: R1 Duration: Fixed-term Job status: Part-time Job starting date: 1. 10. 2025 Application deadline
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electrodes to improve the power density and energy efficiency of redox flow batteries (RFB), enabling affordable and durable long-duration energy storage. The approach is to use hierarchical structures, i.e
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in March 2026 and terminating in December 2029 are offered within a research project “Light Utilization for Matter Emergence” (GM25-16662M) funded by the Czech Science Foundation. The applicants will
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Structure–Sequence Integration for Medical Applications (Ministry of Education, Youth and Sports, Inter-Action programme) Size of workload: 0.2 FTE Length of employment: until 30 September 2028 Minimum
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-time employment of 40 hours per week) Expected Start Date: negotiable with respect to immigration timelines for non EU candidates Number of Open Positions: 1 Application Deadline: 2. 10. 2025
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of Contract: temporary position with 1-year contract (with possible extension), non-academic Working Hours: 1,0 FTE (full-time employment of 40 hours per week) Expected Start Date: negotiable with respect
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, materials science and the use of AI in the analysis and design of novel nanocomposites with a prescribed set of properties. Expectations: Proven track record of publishing in structure-property relationships
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and drug design, do not hesitate to read further. Please, include the following text in the subject of the email with your application: "PhD Position in Structure-Based Drug Design and Machine Learning