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| 001 | 234764 | ||
| 005 | 20201030173028.0 | ||
| 024 | 7 | _ | |2 I:(DE-H235)DIB-20120731 |a G:(DE-HGF)2019_IVF-HIDSS-0002 |d HIDSS-0002 |
| 035 | _ | _ | |a G:(DE-HGF)2019_IVF-HIDSS-0002 |
| 150 | _ | _ | |a DASHH: Data Science in Hamburg - Helmholtz Graduate School for the Structure of Matter |y 2019 - 2025 |
| 371 | _ | _ | |0 P:(DE-H253)PIP1010949 |a Rohringer, Nina |
| 371 | _ | _ | |0 P:(DE-H253)PIP1087358 |a Rarey, Matthias |
| 371 | _ | _ | |0 P:(DE-H253)PIP1087349 |a Le Borne, Sabine |
| 450 | _ | _ | |a HIDSS-0002 |w d |y 2019 - 2025 |
| 510 | 1 | _ | |0 I:(DE-588b)5165524-X |a Helmholtz Gemeinschaft Deutscher Forschungszentren |b HGF |
| 550 | _ | _ | |0 G:(DE-HGF)IVF-20140101 |a Impuls- und Vernetzungsfonds |w t |
| 680 | _ | _ | |a ‘Data Science’ is the science of extracting knowledge from typically large amounts of data. The increasing level of automatization and the increasing number and resolution of sensors in scientific experiments result in large, heterogeneous and highly complex data collections. Therefore, Data Science is seen as a key technology in modern and future natural sciences. Data intensive research in experimental and theoretical science at the Forschungscampus Hamburg-Bahrenfeld requires beyond off-the-shelf software solutions for data management, processing and analysis. Tailored or even completely new computational data science methods are indispensable. At the same time, the challenges ahead will foster new innovative ideas in computer science and applied mathematics. To develop these methods, scientists have to be highly skilled in the corresponding physics domain and computer science alike. The Data Science in Hamburg – Helmholtz Graduate School for the Structure of Matter (DASHH) will be established to address this highly interdisciplinary need. DASHH bundles competences of scientists with high international reputation in basic research for the structure of matter, computer science and applied mathematics in Hamburg in a new and unique fashion. The graduate school covers data challenges from application fields such as structural biology, particle physics, material science and ultrafast X-ray science. These data challenges have in common that they cannot be addressed with standard computational methods, but require modern data science techniques instead. Several areas from computer science and mathematics play important roles, especially data management and engineering, machine learning and data analytics, signal and image processing, algorithm design, optimization and simulation, software engineering and automation and control systems. |
| 856 | 4 | _ | |u https://hgf.desy.de/ivf/projekte/e289393/index_ger.html |y Description |
| 909 | C | O | |o oai:juser.fz-juelich.de:885933 |p authority:GRANT |p authority |
| 909 | C | O | |o oai:juser.fz-juelich.de:885933 |
| 980 | _ | _ | |a G |
| 980 | _ | _ | |a AUTHORITY |
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