2,775 genetic-algorithm-computer "Integreat Norwegian Centre for Knowledge driven Machine Learning" PhD scholarships
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to develop Computer Vision algorithm and Interfaces for collaborations with Historians teams. Specifically, the research will focus on structured data with clear repeated patterns, such as characters in a text
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rare genetic disorders, using both distributed and federated computational approaches. Your key responsibilities include: Analyzing large-scale genomic datasets using innovative computational techniques
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connections to clinicians, patients, and European initiatives such as ERDERA. What sets us apart is our unique position at the interface of bioinformatics, clinical genetics, and patient care. This ensures
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• Characterization of expressed silk fibroins (e.g. SDS-PAGE) • Genetics tools to reprogramme silk (e.g. Crispr/Cas, cloning, microinjections, PCR etc) What you bring to the table • Master of Science (M.Sc.) in
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Primary Supervisor - Prof David S Richardson Scientific Background Genetic variation within populations is essential to their ability to adapt and survive, but most mutations that change function
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you want to contribute to research on marketing communication on TikTok
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(UTC) Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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Your Job: The conventional, manual co-design of algorithms and hardware is slow and inefficient. Our group develops methods and tools to automate the co-design process. The core of this project is
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, algorithms and social media? Then apply for this PhD project focused on demystifying algorithmic persuasion by commercial advertisers on TikTok from a differential vulnerability perspective. Who is vulnerable
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to make viable trading decisions under high price volatility. This PhD position focuses on designing, developing, and evaluating self-learning energy trading algorithms that are able to cope with