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, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems. Project description This PhD project is linked
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Researcher (R1) Country Sweden Application Deadline 17 Nov 2025 - 22:59 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project description Third-cycle subject: Biotechnology As part of
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for hydrogen carrier synthesis. Our vision is to establish an adaptive multiscale platform where catalyst performance is computed from first principles. Contract terms and what we offer The PhD-positions
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departmental duties, up to a maximum of 20 per cent of full-time. Your qualifications You have graduated at Master’s level in Computer Science, Materials Science, Physics, Mathematics, or a related disciplines
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. Personal merits will play an important role in the selection process. Place of work: Uppsala Forms for funding or employment: PhD employment (4 years) Starting date: According to agreement. Application
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biochemistry, especially protein purification, and computational image analysis must be acquired before starting PhD project work. As a PhD candidate, you must also be fluent in both oral and written English
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). Candidates should have a Master’s degree in physical chemistry, computational chemistry, biophysics, computational biology, biochemistry, or equivalent. Candidates should have demonstrated interest in
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purification, and computational image analysis must be acquired before starting PhD project work. As a PhD candidate, you must also be fluent in both oral and written English. Merits are: Skills and experiences
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transcriptomics (Visium HD, Xenium), single-cell RNA sequencing, and computational modeling, the student will map tumor cell states, lineage hierarchies, and differentiation trajectories. Insights from