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language models (LLMs) for educational purposes. Furthermore, the right candidate has a deep understanding of pedagogical research, with focus on how educational processes can be facilitated by AI. The role
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APPLICATION INSTRUCTIONS: CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process . Please do not apply
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evaluation and development of novel PEC systems. · Design and implement in-situ TEM experiments using the available gas and liquid sample holders to study dynamic processes in real-time, under controlled
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will be involved in processing and analysing tissue collected from patients undergoing surgery, using whole genome sequencing, transcriptomics and proteomics. You will be heavily involved in designing
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cover-post-doc-2024 (cu.edu) Qualifications: Minimum Qualifications: Applicants must meet minimum qualifications at the time of hire. PhD or MD/PhD degree in computational biology and genetics, or related
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Postdoc in development and testing of electrodes for liquid alkaline water electrolysis - DTU Energy
multi-physics modelling, autonomous materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD
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of agentic behaviour and publishing high-impact research. Candidates should possess a PhD (or be near completion) in PhD in Computer Science, AI, Security, or a related field. You will have a Strong background
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. Candidates should have a PhD in Biology, Stem Cell Biology, Regenerative Medicine, Biomedical Engineering, or a related field. We welcome applicants with recent PhDs and individuals seeking additional
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program. By incorporating the latest technologies and research methodologies, we aim to revolutionize biomechanics and profoundly impact human health, sports performance, and industrial processes
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Worldwide R&D Projects. Previous experience in one or preferably more topics from these areas is considered a merit: - Multi-modal data processing for decision-making in natural environments - Terrain