Associate Professor in Biopharmachemical Analytics

Associate Professor in Biopharmachemical Analytics

University of Limerick - Department of Biological Sciences

Limerick, Ireland

JOB DESCRIPTION

We are seeking a dynamic and innovative academic researcher at the intersection of biopharma and pharma analytics to join the Department of Biological Sciences as part of the new BSc/MSc Immersive Bioscience and Biotherapeutics (iBio) course team. The candidate will be expected to contribute to the development and implementation of this new programme as well as contributing to existing taught programmes in the Department. The ideal candidate will possess expertise in biopharmaceutical/pharmaceutical science combined with a strong background in advanced analytical techniques, data science, and computational modelling. This position offers an exciting opportunity to lead interdisciplinary research initiatives aimed at advancing the use of bioanalytical methods to improve biopharmaceutical process development and to integrate this knowledge into the innovative iBio BSc/MSc programme, as well as into other existing taught programmes.

The successful candidate will be expected to develop and lead an externally funded independent research programme and to drive impactful research that contributes to the evolving landscape of the biopharma sector, particularly in relation to data-driven solutions for drug discovery, process development, and commercialization.

EXPERIENCE

• Demonstrated expertise in biopharma analytics, pharma analytics, or computational approaches in drug or process development;
• Strong background in data analysis, machine learning, data visualization, and computational modelling relating to biopharma;
• A proven track record of peer-reviewed publications in biopharma, pharmaceutical analytics, or related areas;
• Experience working in interdisciplinary teams involving both academic researchers and industry partners is preferred.

KEY RESPONSIBILITIES:

Research Leadership

• Lead an innovative well-funded research programme at the interface of biopharma and pharma analytics;
• Develop and apply cutting-edge analytical techniques (including Process Analytical Techniques (PAT), machine learning, and big data analytics) to address critical challenges in drug discovery and process development;
• Publish high-quality research findings in top-tier academic journals and present at national and international conferences;
• Work independently and contribute to research centres/groups, such as the Bernal Institute to develop and enhance the field of biopharma data analytics.

Teaching and Mentorship

• Teach undergraduate and graduate-level courses in biopharma, bio/pharmaceutical analytics, data science, and related fields. This will involve the preparation of all necessary material and delivering lectures, workshops, practicals and tutorials face-to-face or online, as well as all grading;
• Supervise graduate students, postdocs, and research assistants in their research and professional development;
• Engage in academic advising and curriculum development to advance the iBio programme’s offerings in the intersection of biopharma and analytics and to contribute to integration of data bioanalytics into existing taught programmes.

Collaboration and Industry Engagement

• Foster partnerships with pharmaceutical companies, research institutions, and governmental organizations;
• Translate research into real-world applications, collaborating with industry stakeholders to drive innovation in biopharma development and bio/process analytics.

Grant Writing and Funding Acquisition

• Secure external research funding through grants and collaborations with industry partners and funding agencies;
• Both lead and, assist in, the preparation of grant proposals and research funding submissions, with a focus on advancing biopharma analytics.

Service

• Assume programme leadership roles that may be allocated to them occasionally by the Head of the Department and take active involvement in curriculum development;
• Input into and lead the development of new level 8 and 9 taught programmes when required;
• Actively participate with the Department of Biological Sciences stakeholders, both internally and externally.

QUALIFICATIONS

Essential Criteria

• Ph.D. (Level 10 NFQ) or equivalent degree in Biopharmaceutical and/or Pharmaceutical Science, Data Science, Computational Biology, or a closely related field.
• Minimum of 3 years (or equivalent) relevant experience post PhD;
• Track record of publishing in relevant peer-reviewed top-tier journals and books by prestigious publishers post PhD in one or more of the following areas biopharma/pharma data analytics, PAT or a closely related field;
• Evidence of teaching at third-level institutions in Biopharmaceutical and/ or Pharmaceutical Science, Data Science, Computational Biology, or a closely related field;
• Advanced Analytical Techniques: Expertise in statistical analysis, PAT, machine learning, or computational modelling as applied to biopharma;
• Data Science Proficiency: Strong programming skills in languages such as R, Python, and MATLAB for data analysis and computational research. Knowledge of software tools for data analysis and visualization (e.g., SAS, SPSS, Tableau, etc.);
• Industry Knowledge: Strong interaction with the biopharmaceutical industry, and knowledge of drug development processes, data analysis for process decision making, and regulatory frameworks;
• Collaboration Skills: Ability to work in interdisciplinary teams involving academic researchers and industry partners;
• Communication Skills: Excellent written and verbal communication skills, including the ability to present complex data and research findings to both academic and non-academic audiences.

Desirable Criteria

• Qualification in teaching to third-level students and knowledge of up-to-date pedagogical practices;
• Evidence of academic course/module material development and delivery in a third-level setting, preferably to bioscience or biomolecular science students;
• Successful track record in supervising Final Year Projects (i.e., BSc), MSc, and/or PhD candidates;
• Experience performing administrative tasks and contributing to periodic departmental and programme reviews and reports;
• Evidence of international collaboration projects and/or publications;
• Evidence of fostering diversity and inclusion in teaching and research;
• Regulatory Knowledge: Understanding of FDA guidelines, EMA regulations, and international standards for production of biological medicaments;
• AI/ML Expertise: Experience applying artificial intelligence and machine learning models to large pharmaceutical datasets to improve process monitoring and development;
• Grant Writing: A successful track record of securing external funding from governmental, philanthropic, or private-sector sources.

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