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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 1 month ago
available here . REQUIRED: PhD in Political Science, Environmental Science, Sociology, Anthropology, History, Economics, Psychology, Computer Science, and related fields earned after September 1, 2023; and
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and coatings. You will be given the opportunity to work collaboratively with a motivated team of early career researchers and PhDs on optical low-adhesion coatings. Within the team, you will be given
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for candidates who wish to broaden their career development. Your skills and attributes for success PhD in Mathematics (or near completion) Strong background in probability theory Ability to conduct independent
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Researcher (R3) Positions PhD Positions Country Poland Application Deadline 5 Oct 2025 - 23:59 (Europe/Warsaw) Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 3 Nov 2025
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receive full support for making connections with other scholars and joining campus intellectual life, as well as mentorship from GSF faculty. Applicants should have PhD in hand by July 1, 2026. In
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sciences in our research. Qualifications The successful candidate has a PhD degree in (Historical) Demography or a related discipline (sociology, geography, economics). Expertise with register data
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at time of application) PhD (or equivalent international degree) or enrolled in a PhD (or equivalent international degree) program. Additional qualifications (required at time of start) • PhD
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-supervising PhD and MSc students working in the project Contributing to new research ideas and (co)-applying for grants Depending on interests and expertise, some teaching on nutritional physiology, microbiome
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22 Sep 2025 Job Information Organisation/Company University College Cork Department HR Research Research Field Biological sciences » Other Researcher Profile Recognised Researcher (R2) Positions PhD
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(ongoing PhD project). These pre-screened datasets will then be analyzed by various machine learning techniques (dimensionality reduction, unsupervised clustering, artificial neural networks, auto-encoders