Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
Materials and Devices (AEMD) group focuses on the material sciences and technology aspects of novel electronic materials, with a strong emphasis on graphene as well as other 2D materials (MoS2). The group
-
technology, nanofabrication) and applications, with a strong emphasis on bioelectronics for neural interfacing. Main Tasks and responsibilities: The research activity of the candidate will be part of
-
Disciplines for Recruitment Science and Engineering: Mathematics, Mechanics, Mechanical Engineering, Material Science and Engineering, Metallurgical Engineering, Control Science and Engineering
-
projects and technical leadership. Basic Qualifications: Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related technical field. Proven experience in
-
of science academies around the world. The University is recruiting scholars focus on artificial intelligence and robotics, data science and big data technology, computer science, statistics, operations
-
. The successful candidate will be joining the international QTWIST program that includes new joint laboratories of Prof. Jarillo-Herrero (MIT) and research groups of Prof. Adrian Bachtold, Prof. Carmen Rubio Verdú
-
Research Engineer - Tools developer for LSQUANT platform (Theoretical and Computational Nanoscience)
different areas of nanoscience and nanotechnology. Job Title: Research Engineer - Tools developer for LSQUANT platform Research area or group: Theoretical and Computational Nanoscience Group Description
-
Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related technical field. A strong publication record, with first-author papers
-
plus Education and training PhD in Bioinformatics or in Biology, Machine Learning, Statistics, Physics, Mathematics, Chemistry or related areas Languages: Highly proficient in both spoken and written
-
widely used by the academic community (about one thousand citations per year), and has been a flagship code of the MaX European Centre of Excellence for exascale computing in Materials Science since its