14 parallel-and-distributed-computing-"LIST" Postdoctoral positions at Purdue University
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, Physics , Quantum Computation , Quantum Computing , Quantum Condensed Matter Theory , Quantum error correction , Quantum Field Theory , Quantum Information , Quantum Information Processing and Communication
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/ : Curriculum Vitae (including a full publication list) Research Statement (two pages maximum + one page for bibliography) Three letters of reference The review of applications will begin on November 15, 2025
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: West Lafayette, Indiana 47907, United States of America [map ] Subject Area: Physics / High Energy Theory Appl Deadline: (posted 2025/10/06, listed until 2026/04/06) Position Description: Apply Position
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communication skills. Strong attention to detail and good organizational skills. Strong desire to work in a collaborative research program. Interested candidates should email Professor Michael Manfra at mmanfra
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: (1) letter of application that includes description of your research interests and experiences, 2) curriculum vitae, (3) a writing sample in English. In addition, candidates should list the names and
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includes description of your research interests and experiences, 2) curriculum vitae, (3) a writing sample in English, and (4) a writing sample in Korean. In addition, candidates should list the names and
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includes description of your research interests and experiences, 2) curriculum vitae, (3) a writing sample in English, and (4) a writing sample in Japanese. In addition, candidates should list the names and
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Qualifications: We seek exceptionally strong candidates with a PhD in statistics, biostatistics, computer science or a related field. Candidates with demonstrated accomplishment in academic research, as can be
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Qualifications: We seek exceptionally strong candidates with a PhD in statistics, biostatistics, computer science or a related field. Candidates with demonstrated accomplishment in academic research, as can be
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning