Staff Engineer - Modeling
Company: Takeda
Location: Boston
Posted on: February 18, 2025
Job Description:
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in my employment application is true to the best of my
knowledge.Job DescriptionOBJECTIVE:Synthetic Molecule Process
Development (SMPD) is responsible for developing robust and
cost-effective processes for manufacturing new small molecule
pharmaceuticals, ensuring high standards of purity and quality
through advanced process design and control strategies. The Staff
Engineer - Process Modeling will join a dynamic and innovative team
of engineers and scientists within SMPD's Process Engineering &
Technology Group, focusing on crystallization modeling and particle
engineering.The successful candidate will have a strong background
in crystallization science, particle engineering, and process
modeling, tackling challenges related to crystal nucleation,
growth, polymorphism, and particle size distribution control. They
will leverage expertise in thermodynamics, kinetics, transport
phenomena, and population balance modeling to develop in-silico
approaches for crystallization process design and optimization.
Additionally, the Staff Engineer will be involved in scale-up and
scale-down modeling of crystallization, wet milling, and
solid-liquid separation processes, integrating both
first-principles and data-driven models.The role includes the
application of process analytical technologies (PAT) in combination
with mathematical models (both mechanistic and statistical) to
enhance process understanding and enable data-rich experimentation.
These approaches will drive the design, optimization, scale-up, and
troubleshooting of crystallization and particle engineering
processes, ensuring robust pharmaceutical manufacturing through
digital and in-silico methodologies.ACCOUNTABILITIES:
- Contributes to the design, development, optimization, and
scale-up of crystallization and particle engineering processes for
synthetic molecule drug substances using process modeling and
simulation principles.
- Utilizes advanced process modeling tools, population balance
models (PBM), and digital twin functionalities, implementing
model-based design of experiments (MBDoE) for process
characterization, risk assessment, and control strategy
development.
- Develops experimental designs and workflows for model
development, validation, and verification, with a focus on crystal
nucleation, growth kinetics, polymorphism control, and particle
size distribution (PSD) engineering.
- Collaborates with cross-functional teams and external partners
to develop and deploy digital twins of crystallization, wet
milling, and solid-liquid separation unit operations.
- Partners with Automation, Manufacturing, Process Engineers, and
PAT experts to develop modeling and simulation (M&S) solutions
that can be deployed across the global organization for in-silico
process design, development, and optimization.
- Recommends, justifies, and implements in-silico tools and an
"in-silico first" approach for crystallization and particle
engineering.
- Authors reports and peer-reviewed manuscripts, conference
presentations.EDUCATION, EXPERIENCE AND SKILLS:Education and
Experience:Required:
- Bachelor's degree in Chemical Engineering, Pharmaceutical
Sciences, or a related field with 5+ years of relevant industry
experience.
- Master's degree in Chemical Engineering, Pharmaceutical
Sciences, or a related field with 3+ years of relevant industry
experience.
- Ph.D. in Chemical Engineering, Pharmaceutical Sciences, or a
related field with 0+ years of relevant industry experience.
- Strong knowledge and understanding of crystallization process
modeling, particle engineering, and polymorph control.
- Strong understanding of population balance models (PBM) for
crystal nucleation, growth, breakage, and aggregation
dynamics.
- Expertise in transport phenomena and thermodynamics as applied
to crystal growth, supersaturation control, and solid-liquid
equilibria.
- Experience with commercially available crystallization and
particle engineering modeling software, such as gPROMS Formulated
Products, Dynochem, or Ansys Fluent.
- Experience with computational fluid dynamics (CFD) modeling for
mixing and solid suspension applications, using software like Ansys
Fluent, Star-CCM+, or MStar CFD.
- Proficiency in data integration from sensors, controllers, and
industrial systems, ensuring real-time process monitoring and
model-based control.
- Experience with programming tools such as MATLAB, Python, R,
SQL, and adherence to good coding practices for model
implementation and automation.Preferred:
- Experience with multivariate analysis (MVA) and Principal
Component Analysis (PCA) for crystallization process
optimization.
- Knowledge of process analytical technologies (PAT) such as
FBRM, Raman, PVM, and UV-Vis for real-time monitoring of
crystallization processes.
- Hands-on experience in wet lab crystallization and particle
size distribution (PSD) characterization.
- Familiarity with Good Manufacturing Practices (cGMP) and
regulatory requirements for model-based submissions.
- Understanding of digital twin applications in process
development and scale-up.
- Experience in machine learning (ML) or AI-assisted modeling
approaches for process optimization.Knowledge and Skills:
- Analytical and Problem-Solving Skills - Ability to troubleshoot
crystallization and particle engineering challenges, analyze
model-based results, and propose effective solutions.
- Teamwork - Capable of working effectively in a highly
cross-functional environment, engaging with process engineers,
chemists, data scientists, and regulatory teams.
- Communication Skills - Clearly conveys technical concepts,
summarizes modeling insights concisely, and adjusts communication
style based on audience. Strong technical writing skills for
scientific reports, regulatory documents, and publications.
- Organization and Time Management - Ability to prioritize
multiple tasks and successfully manage work across individual,
departmental, and corporate goals.
- Knowledge Sharing - Effectively captures and transfers
organizational knowledge, contributing to model libraries, process
databases, and training programs for broader adoption of in-silico
tools.
- Resource Management - Manages time and technical resources
efficiently, including external collaborations with vendors,
research institutions, and software providers.
- External Involvement - Actively contributes to the scientific
community through conference presentations, scientific
publications, and professional workshops.
- Technical Expertise - Demonstrates subject matter expertise in
crystallization modeling, population balance modeling, and
in-silico process development, leveraging advanced simulation tools
for process design and optimization.Takeda Compensation and
Benefits SummaryWe understand compensation is an important factor
as you consider the next step in your career. We are committed to
equitable pay for all employees, and we strive to be more
transparent with our pay practices.For Location:Boston, MAU.S. Base
Salary Range:$108,500.00 - $170,500.00The estimated salary range
reflects an anticipated range for this position. The actual base
salary offered may depend on a variety of factors, including the
qualifications of the individual applicant for the position, years
of relevant experience, specific and unique skills, level of
education attained, certifications or other professional licenses
held, and the location in which the applicant lives and/or from
which they will be performing the job.The actual base salary
offered will be in accordance with state or local minimum wage
requirements for the job location.U.S. based employees may be
eligible for short-term and/or long-termincentives. U.S.based
employees may be eligible to participate in medical, dental, vision
insurance, a 401(k) plan and company match, short-term and
long-term disability coverage, basic life insurance, a tuition
reimbursement program, paid volunteer time off, company holidays,
and well-being benefits, among others. U.S.based employees are also
eligible to receive, per calendar year, up to 80 hours of sick
time, and new hires are eligible to accrue up to 120 hours of paid
vacation.EEO StatementTakeda is proud in its commitment to creating
a diverse workforce and providing equal employment opportunities to
all employees and applicants for employment without regard to race,
color, religion, sex, sexual orientation, gender identity, gender
expression, parental status, national origin, age, disability,
citizenship status, genetic information or characteristics, marital
status, status as a Vietnam era veteran, special disabled veteran,
or other protected veteran in accordance with applicable federal,
state and local laws, and any other characteristic protected by
law.LocationsBoston, MAWorker TypeEmployeeWorker
Sub-TypeRegularTime TypeFull timeJob ExemptYesIt is unlawful in
Massachusetts to require or administer a lie detector test as a
condition of employment or continued employment. An employer who
violates this law shall be subject to criminal penalties and civil
liability.
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Keywords: Takeda, Boston , Staff Engineer - Modeling, Engineering , Boston, Massachusetts
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