Professor in Computational Modelling and Data Analytics

at  National Institute for Bioprocessing Research and Training NIBRT

VACANCY SUMMARY

NIBRT invites applications for the prestigious UL/NIBRT Professor in Computational Modelling and Data Analytics in the Department of Chemical Sciences.
UL/NIBRT Professor in Computational Modelling and Data Analytics will be a Principal Investigator in the Department of Chemical Sciences playing a key leadership role in SSPC, the Science Foundation Ireland national research centre for pharmaceuticals and biopharmaceuticals. The role will be jointly appointed with NIBRT, the National Institute for Bioprocessing Research and Training, under an interinstitutional strategic partnership agreement.

REQUIRED SKILLS & COMPETENCIES

The Professor in Computational Modelling and Data Analytics will demonstrate leadership in internationally leading research that can address industry challenges. They will have rich experience in collaborative,cross-disciplinary work and in scientific outreach. They will systematically strive to connect fundamental and applied research to meet the needs of the national research landscape, while at the same time, firmly embedding their expertise in international research efforts. The Professor will contribute to attract and train graduate students and to lead postgraduate and postdoctoral research teams at the Department of Chemical Sciences at University of Limerick and at NIBRT.
The post holder will actively contribute to the development of significant research and teaching initiatives across University of Limerick and at NIBRT.

ROLE PURPOSE

UL-NIBRT Professor in Computational Modelling and Data Analytics will be a Principal Investigator in the Department of Chemical Sciences playing a key leadership role in SSPC, the Science Foundation Ireland national research centre for pharmaceuticals and biopharmaceuticals. The role will be jointly appointed with NIBRT, the National Institute for Bioprocessing Research and Training, under an interinstitutional strategic partnership agreement.
The Professor in Computational Modelling and Data Analytics will hold a 40% joint appointment with NIBRT, the National Institute for Bioprocessing Research and Training. The Professor in Computational Modelling and Data Analytics will be a specialist in computational science and/or data analytics applied to pharmaceutical and biopharmaceutical manufacturing, with a strong emphasis on advanced therapeutics including cell and gene therapies. They should demonstrate expertise in advanced computational modelling methods (for example, but not limited to, Bayesian decision theory, large-scale molecular dynamics,
computational fluid dynamics) and/or statistical methods including machine learning approaches.
The Professor will collaborate across the university as appropriate, including colleagues in the Mathematical Application Consortium for Science and Industry (MACSI) in the Department of Mathematics and Statistics and Lero, the Irish Software Centre, hosted in UL. They will apply high-performance computing (HPC) enabled state of the art methods working in partnership with academic and industry partners, and they will strive to further develop these methods with respect to their statistical and methodological foundations. The Professor will have demonstrated clear focus on the application of these methods to fundamental research questions that impact pharma and biopharma manufacturing.
As an academic professor, the postholder will (i) help drive the strategic direction and academic mission (research/innovation and teaching) of the Department of Chemical Sciences, SSPC Centre and the Bernal Institute (ii) will work closely with researchers at MACSI, (iii) will conduct research at and building partnerships with NIBRT. Hosted within the Faculty of Science and Engineering at UL, the appointed candidate will hold a senior academic role within the discipline of Computational Modelling and Data Analytics.

KEY RESPONSIBILITIES

The successful candidate will demonstrate excellence in the following essential key areas:

• Expertise in state-of-the-art computational modelling and/or data analytics including machine learning,applied to pharma and biopharma
• Experience in the analysis of large, multidimensional data sets collected in a pharmaceutical setting
• In-depth knowledge of biological manufacturing processes, including cell and gene therapy production
• Experience with interdisciplinary research
• Experience with public outreach
• Visibility in the scientific community