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Field
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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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, algorithms, and tools for spoken language-based detection of clinical change. General information about the position: The position is fixed term for a duration of three years. Appointment to the position
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learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial analysis Strong publication record Experience in women and children’s
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potential research topics to improve the project results. Research topics may include interventions in public services, labor markets, marketing, and digital platforms, using large-scale data and algorithmic
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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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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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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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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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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