Research Output per year
Research Output per year
Project Details
Description
MSCA FIRE: Fellows with Industrial Research Enhancement
The FIRE programme is an integrated 4 year Doctoral Training programme, bringing together two national Centres for Doctoral Training: the Centre for Sustainable Chemical Technologies and the Centre for Digital Entertainment.
The objectives of MSCA FIRE are to increase the international aspects of these successful intersectoral and inter-disciplinary programmes and to develop the elements of transnational mobility and career development, common to our industry facing doctoral programmes.
Objectives are to:
- Offer FIRE Fellows the benefits of two established national Doctoral Training Centres, as they expand their international company placement activities.
- Bring Fellows the benefits of the cross-sectoral reach of both Centre, with vibrant industries.
- Enhance interdisciplinarity and offer added-value training practices beyond their specialised research area, to all fellows.
- Use these synergies to fire-up the fellows to become autonomous, creative, highly-skilled and fully ready for careers in international industries.
This will be achieved by:
- Implementing a combined 4 year doctoral training programme,
- using two existing national Doctoral Training Centres and their already engaged industrial partners.
MSCA FIRE will deliver:
- 20 autonomous, creative, highly-skilled scientists and engineers fully ready for careers in international industries, and
- A model for intersectoral, interdisciplinary doctoral training in an international environment.
Industrial partners ensure that research carried out is relevant and will enhance employability of graduates, both in Europe and globally.
The FIRE programme is an integrated 4 year Doctoral Training programme, bringing together two national Centres for Doctoral Training: the Centre for Sustainable Chemical Technologies and the Centre for Digital Entertainment.
The objectives of MSCA FIRE are to increase the international aspects of these successful intersectoral and inter-disciplinary programmes and to develop the elements of transnational mobility and career development, common to our industry facing doctoral programmes.
Objectives are to:
- Offer FIRE Fellows the benefits of two established national Doctoral Training Centres, as they expand their international company placement activities.
- Bring Fellows the benefits of the cross-sectoral reach of both Centre, with vibrant industries.
- Enhance interdisciplinarity and offer added-value training practices beyond their specialised research area, to all fellows.
- Use these synergies to fire-up the fellows to become autonomous, creative, highly-skilled and fully ready for careers in international industries.
This will be achieved by:
- Implementing a combined 4 year doctoral training programme,
- using two existing national Doctoral Training Centres and their already engaged industrial partners.
MSCA FIRE will deliver:
- 20 autonomous, creative, highly-skilled scientists and engineers fully ready for careers in international industries, and
- A model for intersectoral, interdisciplinary doctoral training in an international environment.
Industrial partners ensure that research carried out is relevant and will enhance employability of graduates, both in Europe and globally.
| Status | Active |
|---|---|
| Effective start/end date | 1/10/15 → 30/03/21 |
Funding
- EU - Horizon 2020
Research Output
- 2 Conference contribution
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Ranking CGANs: Subjective Control over Semantic Image Attributes
Saquil, Y., Kim, K. I. & Hall, P., 6 Sep 2018, Proc. of British Machine Vision Conference (BMVC). British Machine Vision AssociationResearch output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access -
Unsupervised Attention-guided Image-to-Image Translation
Alami Mejjati, Y., Richardt, C., Tompkin, J., Cosker, D. & Kim, K. I., 31 Dec 2018, Advances in Neural Information Processing Systems 31 (NIPS), 2018. Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N. & Garnett, R. (eds.). Neural Information Processing Systems Foundation, Inc., p. 1-22 22 p. (NIPS Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open Access62 Citations (Scopus)
Datasets
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Dataset for ''Screen printed carbon CsPbBr3 perovskite solar cells with high open-circuit photovoltage''
Poli, I. (Creator) & Cameron, P. (Creator), University of Bath, 13 Sep 2018
DOI: 10.15125/BATH-00530
Dataset
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Dataset for Enhancing the hydrophobicity of perovskite solar cells using C18 capped CH3NH3PbI3 nanocrystals
Poli, I. (Creator), Poli, I. (Data Collector), Cameron, P. (Creator), Cameron, P. (Project Leader), Eslava Fernandez, S. (Supervisor), Liang, X. (Data Collector) & Baker, R. (Data Collector), University of Bath, 26 Jun 2018
DOI: 10.15125/BATH-00499
Dataset
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Dataset for ''Tetrabutyl ammonium cation for moisture-resistant and semitransparent perovskite solar cells''
Poli, I. (Creator), Cameron, P. (Supervisor) & Eslava Fernandez, S. (Supervisor), University of Bath, 2017
DOI: 10.15125/BATH-00403
Dataset