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Field
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: The successful applicant will be responsible for: Obtaining rigorous mathematical results at the interface of optimization, geometry, and data science Designing, implementing, and testing algorithms Engaging in
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bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
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apply cutting-edge machine learning algorithms, with focus on foundation models and LLMs/agents, to analyze complex biological data. This data includes gsingle cell genomics profiles, spatial data, and
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work alongside renowned academics and researchers in ENU’s School of Computing, Engineering and the Built Environment. If you are someone with expertise in multimodal speech processing and AI algorithms
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operation of the umFm module unit used in vertical farm which includes handling of soil compost, irrigating of the crops and taking note of the sensors incorporation in the vertical farm inhouse. Job
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computer programming to verify the efficiency of the designed solution algorithms Analyze data acquired from the field survey Develop machine learning models for prediction and recommendation Job
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amplifiers Develop scripts and algorithms for analog IC design Prepare report and conduct presentation at seminars Assist the school in various teaching activities, including instructing or supervision of labs
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models, algorithms, and tools for spoken language-based detection of schizophrenia relapse in 6 different languages. Start date: The workplace is at UiT in Tromsø. You must be able to start in the position
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HiPerBreedSim project. In this role, you will leverage recent advances in working with ancestral recombination graphs (ARGs) to develop algorithms and code for simulating population genomic data, including
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Condensed Matter Physics and Materials Sciences o Theoretical and Computational Biophysics o Soft Matter Physics o Physical Chemistry and Theoretical Chemistry o Combinatorics, Algorithm, Extremal Graph