Kaizen RecruitmentDublin
Experience working in a Fast-Paced Production Environment Qualifications: - 1-2 years experience working in a production position preferred. Anti Static/Anti Slip Boots are required with Certificate to prove Skills: Production forklift driver time keeping.
...
VickerstockDublin
pharmaceutical projects. Your expertise will contribute to the success of our team, ensuring the seamless execution of projects that define the future of pharmaceutical manufacturing.
Key Responsibilities:
• Lead the on-site team in executing construction...
Jazz PharmaceuticalsDublin
working in the pharmaceutical industry in technical and / or process statistical role.
• Experience working in cross functional teams in a pharmaceutical industry environment.
• Record of achievement in pharmaceutical manufacturing environment
• Project...
Daksta RecruitmentLeinster
Daksta are looking for a Lead CQV Consultant for an 18-Month contract opportunity in Geneva. The Project is a large Pharmaceutical manufacturing facility.
Responsibilities
• Commissioning, Qualification and Validation of the project
• Documentation...
Daksta RecruitmentDublin
Daksta are looking for a Lead CQV Consultant for an 18-Month contract opportunity in Geneva. The Project is a large Pharmaceutical manufacturing facility.
Responsibilities
• Commissioning, Qualification and Validation of the project
• Documentation...
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Senior Scientist: Process Modelling and Hybrid Modelling New
CPL | Dublin | www.cpl.com |
Cpl in partnership with our client Pfizer Grange Castle are currently recruiting for a
Senior Scientist: Process Modelling and Hybrid Modelling
The Manufacturing Intelligence (MI) team within Pfizer’s Global Technology & Engineering (GT&E) is responsible for driving the development and implementation of advanced analytics including AI/ML, soft sensor, advanced process control, and process condition monitoring solutions in support of manufacturing and future capabilities in Pfizer Global Supply (PGS).
As a member of MI, this role will have the opportunity to develop and implement advanced analytics, real-time soft sensors, machine learning, advanced process control and IIoT solutions/capabilities in manufacturing settings to achieve actionable insights and enable continued improvement for pharmaceutical manufacturing and quality operations.
Responsibilities
• Technical contribution to high-impact projects that require data analytics, advanced modelling, and optimization expertise.
• Identify high value opportunities for applying Advanced Analytics, Advanced Process Control (APC), Artificial Intelligence (AI), Machine Learning (ML) and Industrial Internet of Things (IIoT), and develop and deploy innovative fit-for-purpose solutions in manufacturing environment
• Drive development of mathematical and machine learning models and support GMP implementation of such analytics solutions
• Apply engineering principles, modelling tools, and experimental skills using data-rich lab/pilot/manufacturing equipment to improve process understanding and facilitate real-time process monitoring and control
• Collaborate with cross-functional teams and key stakeholders, effectively communicate progress to management, and drive project progress in a timely manner.
Basic Qualifications
• A PhD degree in relevant engineering major, mathematics, or computer science is preferred.
• Expert-level knowledge in Python is a must. Experience in any of the following languages is a plus: R, Matlab, JavaScript.
• Ability to perform data engineering on real world big-data ranging from structured time-series datasets with thousands of features, to unstructured image, text, audio and video data.
• Track record in applying data science and machine learning methodologies to real-world data to generate insight and support decision-making.
• Ability to work collaboratively in diverse cross-functional teams on innovative solutions and tools with an open attitude towards fast learning
• Knowledge of upstream and downstream Biopharmaceutical Manufacturing
• Expertise in first principles (thermodynamics, reaction modelling, heat transfer, mass transfer principles, cell growth), hybrid modelling. Ability to develop practical process models for real-time applications is a strong plus.
• Demonstrated experience of story-telling to technical experts and non-technical stakeholders
• Familiarity with feedback control algorithms, real-time communication protocols, industrial process historians, and industrial automation platforms such as DeltaV and ASPEN.
• Independent, self-motivated personality with excellent oral and written communication skills
Preferred Qualifications
• Expertise in first principles (thermodynamics, reaction modelling, heat transfer, mass transfer principles), hybrid modelling. Ability to develop practical process models for real-time applications is a strong plus.
• Experience in cloud-based code development and deployment environments such as AWS SageMaker or Tibco.
• Familiarity with cloud computing based data-warehouses such as Snowflake or Redshift, and relational SQL databases.
• Hands-on experience in deep learning and LVM for real-time monitoring and anomaly detection of time-series data and automated root cause analysis.
• Experience in data visualization and real-time GUIs using Streamlit, Plotly, Spotfire, etc.
• Familiarity with feedback control algorithms, real-time communication protocols, industrial process historians, and industrial automation platforms such as DeltaV and ASPEN.
• Knowledge of Cell Culture, Fermentation and Vaccines Conjugation
• Work Location Assignment: Flexible - USA
Senior Scientist: Process Modelling and Hybrid Modelling
The Manufacturing Intelligence (MI) team within Pfizer’s Global Technology & Engineering (GT&E) is responsible for driving the development and implementation of advanced analytics including AI/ML, soft sensor, advanced process control, and process condition monitoring solutions in support of manufacturing and future capabilities in Pfizer Global Supply (PGS).
As a member of MI, this role will have the opportunity to develop and implement advanced analytics, real-time soft sensors, machine learning, advanced process control and IIoT solutions/capabilities in manufacturing settings to achieve actionable insights and enable continued improvement for pharmaceutical manufacturing and quality operations.
Responsibilities
• Technical contribution to high-impact projects that require data analytics, advanced modelling, and optimization expertise.
• Identify high value opportunities for applying Advanced Analytics, Advanced Process Control (APC), Artificial Intelligence (AI), Machine Learning (ML) and Industrial Internet of Things (IIoT), and develop and deploy innovative fit-for-purpose solutions in manufacturing environment
• Drive development of mathematical and machine learning models and support GMP implementation of such analytics solutions
• Apply engineering principles, modelling tools, and experimental skills using data-rich lab/pilot/manufacturing equipment to improve process understanding and facilitate real-time process monitoring and control
• Collaborate with cross-functional teams and key stakeholders, effectively communicate progress to management, and drive project progress in a timely manner.
Basic Qualifications
• A PhD degree in relevant engineering major, mathematics, or computer science is preferred.
• Expert-level knowledge in Python is a must. Experience in any of the following languages is a plus: R, Matlab, JavaScript.
• Ability to perform data engineering on real world big-data ranging from structured time-series datasets with thousands of features, to unstructured image, text, audio and video data.
• Track record in applying data science and machine learning methodologies to real-world data to generate insight and support decision-making.
• Ability to work collaboratively in diverse cross-functional teams on innovative solutions and tools with an open attitude towards fast learning
• Knowledge of upstream and downstream Biopharmaceutical Manufacturing
• Expertise in first principles (thermodynamics, reaction modelling, heat transfer, mass transfer principles, cell growth), hybrid modelling. Ability to develop practical process models for real-time applications is a strong plus.
• Demonstrated experience of story-telling to technical experts and non-technical stakeholders
• Familiarity with feedback control algorithms, real-time communication protocols, industrial process historians, and industrial automation platforms such as DeltaV and ASPEN.
• Independent, self-motivated personality with excellent oral and written communication skills
Preferred Qualifications
• Expertise in first principles (thermodynamics, reaction modelling, heat transfer, mass transfer principles), hybrid modelling. Ability to develop practical process models for real-time applications is a strong plus.
• Experience in cloud-based code development and deployment environments such as AWS SageMaker or Tibco.
• Familiarity with cloud computing based data-warehouses such as Snowflake or Redshift, and relational SQL databases.
• Hands-on experience in deep learning and LVM for real-time monitoring and anomaly detection of time-series data and automated root cause analysis.
• Experience in data visualization and real-time GUIs using Streamlit, Plotly, Spotfire, etc.
• Familiarity with feedback control algorithms, real-time communication protocols, industrial process historians, and industrial automation platforms such as DeltaV and ASPEN.
• Knowledge of Cell Culture, Fermentation and Vaccines Conjugation
• Work Location Assignment: Flexible - USA
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