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- MOHAMMED VI POLYTECHNIC UNIVERSITY
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programming languages like OCaml will be expected from successful applicants. We offer: Postdoctoral position for 1-3 year. (TVÖD E13) / PhD position for 3 years (comparable to 65% TVÖD E13). No teaching duties
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offers a postdoctoral research training program. The department supports an array of faculty directed research programs of which many are supported by extramural grants and/or contracts. The department
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, architecture, and/or industrial design. You also possess: Strong analytical skills and innovative attitude Previous experience with finite element simulations and/or rapid prototyping Good programming and image
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familiarity with associated technologies. Demonstrated programming proficiency in languages such as Java and Python, along with experience in various development environments. Knowledge of participating in
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: Ability to manage a research programme financially and administratively under the guidance of the Principal Investigator. Ability to work independently with excellent problem-solving skills, collaborate
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Systems, Differential Geometry and/or Information Theory. Excellent academic credentials. Experience with programming languages (such as Python, Julia, Matlab, C/C++, etc.). Strong knowledge and interest in
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Process Engineering Department (CBS) is an entity of the Mohammed VI Polytechnic University (UM6P). The main objective of CBS is to set up a distinctive research-teaching program of international level, in
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and independently plan scientific research, as well as collaborate with other project members. Excellent proficiency in English, both oral and written. Meriting Qualifications: Experience in
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, international environment. Excellent spoken and written English (our working language). We offerPositions are available from fall 2025 (negotiable) with an internationally competitive salary and benefits
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Nature Careers | Vancouver South Shaughnessy NW Oakridge NE Kerrisdale SE Arbutus Ridge, British Columbia | Canada | about 2 months ago
, mathematics, and data science. Collaborative projects merge traditional geographic research with advanced computational methods such as graph neural networks (GNNs) and large language models (LLMs) to explore