Biologics Process Modeller
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- Masters or PhD in Chemical Engineering, or a related technical field, with 1-4 years of research experience in modeling, optimization and control of bioprocesses
- Posting language
- English
- Posted
Original job description
About Basetwo
Basetwo is building the AI layer for pharmaceutical and chemical manufacturing. Our AI-powered digital twin platform helps manufacturers accelerate the journey from lab to commercial production through faster scale-up/tech transfer, and de-risked quality control. Trusted by leading global manufacturers, we're bringing modern AI to one of the world's most complex and impactful industries. Our team combines expertise across chemical engineering, manufacturing, AI, and software to tackle high-impact industrial problems.
The Role
Simulation is at the heart of the Basetwo platform, and our science team is looking to bring on an expert in Process Modelling who will be able to make significant technical contributions to our process simulation engine. The Process Modeller will be responsible for developing mathematical models for the Basetwo platform to solve modelling and control applications in pharmaceuticals and biologics manufacturing. Our ideal candidate will partner with our Customer's subject matter experts (SMEs) and our Engineering team to deliver product-driven simulation solutions to solve customer challenges.
What You'll Do
As a Process Modeller, you will:
This role is a fit for someone whose core expertise is in bioprocesses and pharma/biologics manufacturing. To be successful in this role you will have:
Basetwo is building the AI layer for pharmaceutical and chemical manufacturing. Our AI-powered digital twin platform helps manufacturers accelerate the journey from lab to commercial production through faster scale-up/tech transfer, and de-risked quality control. Trusted by leading global manufacturers, we're bringing modern AI to one of the world's most complex and impactful industries. Our team combines expertise across chemical engineering, manufacturing, AI, and software to tackle high-impact industrial problems.
The Role
Simulation is at the heart of the Basetwo platform, and our science team is looking to bring on an expert in Process Modelling who will be able to make significant technical contributions to our process simulation engine. The Process Modeller will be responsible for developing mathematical models for the Basetwo platform to solve modelling and control applications in pharmaceuticals and biologics manufacturing. Our ideal candidate will partner with our Customer's subject matter experts (SMEs) and our Engineering team to deliver product-driven simulation solutions to solve customer challenges.
What You'll Do
As a Process Modeller, you will:
- Work closely with customer's SMEs to understand their process challenges, identify technical requirements and implement advanced modeling solutions
- Research, develop and validate mathematical models for industrial processes in pharmaceuticals and biologics manufacturing
- Contribute to product development as it relates to process simulation in collaboration with cross-functional teams, supporting roadmaps and feature iterations based on customer feedback
- Advocate for best practices among the modeling and simulation team
- Document research activities and model structure in well-structured product specification documents
This role is a fit for someone whose core expertise is in bioprocesses and pharma/biologics manufacturing. To be successful in this role you will have:
- Masters or PhD in Chemical Engineering, or a related technical field, with 1-4 years of research experience in modeling, optimization and control of bioprocesses
- Hands-on experience with metabolic flux analysis (MFA) and/or dFBA is a strong asset
- Strong foundation in core chemical engineering fundamentals, including chemical kinetics, thermodynamics, and transport phenomena is a must
- Ability to develop research-grade code in Python leveraging scientific computing libraries
- Demonstrated track record of starting and leading interdisciplinary research and engineering projects
- Experience communicating projects to both technical and non-technical audiences, and working on cross-functional teams
- Product-driven thinking - an ability to map customer pain points to product features
More about this job
Responsibilities
Develop, research, and validate mathematical models for pharmaceutical and biologics manufacturing processes, contributing to Basetwo’s process simulation engine and product development. Partner with customer subject matter experts and cross-functional teams to translate process challenges into simulation solutions, document model structures, and promote modeling best practices.
Requirements
A master’s or PhD in Chemical Engineering or a related technical field is required, along with 1–4 years of research experience in bioprocess modeling, optimization, and control. Candidates need strong chemical engineering fundamentals and Python scientific-computing skills; hands-on experience with metabolic flux analysis or dFBA is an asset, as are interdisciplinary project leadership and the ability to communicate with technical and non-technical audiences.
Skills
- Bioprocess Modeling
- Pharmaceutical Manufacturing
- Biologics Manufacturing
- Mathematical Modeling
- Process Simulation
- Optimization
- Process Control
- Metabolic Flux Analysis
- Dynamic Flux Balance Analysis
- Chemical Kinetics
- Thermodynamics
- Transport Phenomena
- Python
- Scientific Computing
- Interdisciplinary Project Leadership
- Cross-Functional Communication
Visa sponsorship
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Categories
- Engineering
- Science & Research
- Manufacturing
- Technology
- Data & Analytics
Keywords
- Bioprocesses
- Pharmaceutical Manufacturing
- Biologics Manufacturing
- Process Modeling
- Mathematical Models
- Process Simulation
- Modeling and Control
- Optimization
- Metabolic Flux Analysis
- Dynamic Flux Balance Analysis
- Chemical Engineering
- Chemical Kinetics
- Thermodynamics
- Transport Phenomena
- Python
- Scientific Computing Libraries
- Digital Twins
- Artificial Intelligence
- Product Development
- Customer Subject Matter Experts
- Cross-Functional Teams
- Research and Validation
- Product Specifications
- Scale-Up
- Technology Transfer
- Quality Control