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. Funding providers: ESRC and Lancaster University. Subject areas: Law, linguistics, social sciences. Project start date: 1st October 2024 (Enrolment from mid-September) Lead Supervisor: Professor Lauren
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providers: ESRC and Lancaster University. Subject areas: Law, linguistics, psychology, sociology, computer science and cognate disciplines. Project start date: 1st October 2024 (Enrolment from mid-September
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, national origin, sex, disability, age, sexual orientation, gender identity or gender expression, veteran status, pregnancy or any other basis protected under applicable law. In accordance with applicable
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theoretical and practical work in various aspects of the family justice system. Funding providers: Economic and Social Research Council (ESRC) and Lancaster University. Subject areas: Law, linguistics, social
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@ssmeridionale.it. Subject area(s): Archaeology; Classical Studies; Comparative Literature; Contemporary History; Cultural Studies; European History; Early Modern History, Humanities; Law and Legal History
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their supervisor in compliance with Federal and State Laws.
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information will be used in a confidential, non-discriminatory manner consistent with state and federal law. The University of Arkansas is an equal opportunity, affirmative action institution. The University
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mimics the empirical laws observed for tectonic seismicity (Gutenberg-Richter law, Omori’s law, interevent time distribution). The model needs to be tuned to a specific field situation where induced
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data partition is contributed by a different party (such as banks, or law enforcement agencies). Two facts about most PETs exist: (i) the output of PETs reveals some information about the parties
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Federated Learning (FL) allow parties to collaboratively analyze a collection of data partitions where each data partition is contributed by a different party (such as banks, or law enforcement agencies). Two