Objective
The advent of the big data era in chemistry and the life sciences requires the development of new computational analysis methods, which are not only of scientific, but also economic relevance. Currently, the international data market already grows six times faster than the entire IT sector, and growth rates further increase. Achieving and sustaining a leadership positions in the big data arena represent critically important challenges for the EU. The economic developments in the emerging big data field are science-driven. Due to complexity and heterogeneity of biochemical and biomedical data, large-scale data exploration and exploitation are intrinsically interdisciplinary tasks. BIGCHEM positions itself at interfaces between chemistry, computer science, and the life science to provide well-structured multidisciplinary training and educate high-in-demand computational specialists capable of operating in interdisciplinary and international research and business settings. Cornerstones of BIGCHEM’s curriculum include on-line lectures and periodic schools taught by internationally leading experts in chemical and life science informatics, a balanced consortium of academia, SMEs, and large industry, and an unprecedented symbiosis of academic and industrial training and application components. Accordingly, BIGCHEM is well positioned to boost multilateral collaborations between academia and industry and train scientists who are highly competitive in the international big data market. In BIGCHEM’s R&D and training activities, the development and evaluation of conceptually novel methods for large-scale data analysis, knowledge extraction, and information sharing with demonstrated practical application potential take center stage. The network has a clearly defined policy for exploitation of new IP through wide involvement of target users, SMEs, and large industry facilitated by the experienced technology transfer department of the coordinator's team.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- medical and health sciences basic medicine pharmacology and pharmacy drug discovery
- natural sciences computer and information sciences data science big data
- natural sciences computer and information sciences artificial intelligence machine learning reinforcement learning
- natural sciences chemical sciences
- natural sciences computer and information sciences artificial intelligence computational intelligence
You need to log in or register to use this function
We are sorry... an unexpected error occurred during execution.
You need to be authenticated. Your session might have expired.
Thank you for your feedback. You will soon receive an email to confirm the submission. If you have selected to be notified about the reporting status, you will also be contacted when the reporting status will change.
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
See all projects funded under this programme -
H2020-EU.1.3.1. - Fostering new skills by means of excellent initial training of researchers
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-ITN-EID - European Industrial Doctorates
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-ITN-2015
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
85764 Neuherberg
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.