You will join as a Scientific Machine Learning Engineer specializing in chemistry applications, working at the interface between graph machine learning, quantum algorithms, and industrial use cases.
You will join as a Scientific Machine Learning Engineer specializing in chemistry applications, working at the interface between graph machine learning, quantum algorithms, and industrial use cases.
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Can perform required responsibilities of this job role and the job role of Associate Machine ... Engages in and promotes a learning culture at thyssenkrupp by sharing knowledge and training other ...
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Computational chemists within AbbVie's MPPD organization work collaboratively with other functions ... Familiarity with machine learning or neural network packages including but not limited to Scikit ...
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Computational chemists within AbbVie's MPPD organization work collaboratively with other functions ... Familiarity with machine learning or neural network packages including but not limited to Scikit ...
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$17 - $18.25/hr
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Associate Machine Learning Chemistry information
What is the difference between Associate Machine Learning Chemistry vs Associate Data Scientist?
| Aspect | Associate Machine Learning Chemistry | Associate Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or Master's in Chemistry, Data Science, or related fields; familiarity with ML frameworks | Bachelor's or Master's in Data Science, Statistics, Computer Science; programming skills in Python/R |
| Work Environment | Research labs, pharmaceutical or chemical companies, biotech firms | Tech companies, finance, healthcare, consulting firms |
| Employer & Industry Usage | Used in industries applying ML to chemical data, drug discovery, materials science | Applied across industries analyzing large datasets, predictive modeling |
Associate Machine Learning Chemistry focuses on applying machine learning techniques specifically to chemical and scientific data, often within research or pharmaceutical settings. In contrast, Associate Data Scientist has a broader scope, working with various data types across multiple industries. Both roles require strong analytical skills and familiarity with ML tools, but their industry focus and data types differ.
What is an associate machine learning chemistry?
How does an associate machine learning chemistry professional typically collaborate with research scientists and engineers?
What are the key skills and qualifications needed to thrive as an associate machine learning chemistry, and why are they important?
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Full-time
Posted 9 days ago
Job description
PASQAL has partnerships with key users in the fields of energy, IT, finance, drug and chemical design, automotive. The maturity and potential of our technology and the quality of our scientific team has been rewarded several times at French, European and global levels.
Description
We are looking for a Quantum Solutions Engineer to join our Quantum Applications department and build client-facing solutions based on PASQAL's quantum algorithm portfolio.
This application-driven engineering role focuses on adapting, integrating, and validating quantum and quantum-enhanced machine learning methods for real-world partner and client use-cases, with a strong focus on molecular and chemical applications.
The goal is to turn PASQAL's existing methods into reliable client deliverables by combining scientific machine learning, Graph Machine Learning, and analog quantum computing.
Contributions to internal method improvement are welcome when they directly support project outcomes.
You will join as a Scientific Machine Learning Engineer specializing in chemistry applications, working at the interface between graph machine learning, quantum algorithms, and industrial use cases.
With strong engineering skills and an interest in quantum computing (physics background is a plus), you will:
• Adapt and implement PASQAL's existing quantum and quantum-enhanced Graph ML algorithms for client datasets, scientific constraints, and performance targets.
• Translate scientific and chemical use cases into well-defined machine learning tasks, such as molecular property prediction, classification, ranking, or candidate screening.
• Select and implement suitable representations for molecules and chemical systems, including physicochemical descriptors, fingerprints, molecular graphs, and quantum feature representations.
• Integrate ML pipelines with quantum execution workflows, emulation and simulation platforms, PASQAL QPUs, and internal tooling.
• Collaborate closely with internal R&D teams to transfer quantum methods from research to application, clarify their assumptions and limitations, and select the most appropriate approach from PASQAL's portfolio.
• Work closely with chemistry experts from clients and partners to understand the scientific meaning, quality, and limitations of molecular and experimental data.
• Produce maintainable code, technical documentation, benchmark reports, and handover material so delivered solutions can be reproduced, reused, and supported.
• Maintain an active scientific and technological watch in Quantum Machine Learning, Graph Machine Learning, and molecular machine learning.
This list is non exhaustive.
About you
- Master's degree or PhD in Machine Learning, Computational Chemistry or Quantum Physics
- 2+ years of experience in a similar role
- Strong ML engineering background, including model training and evaluation, classical baselines, metrics, and reproducible experimentation.
- Hands-on experience with graph-structured data and Graph Machine Learning, such as graph kernels, Graph Neural Networks, or graph representations.
- Familiarity with quantum computing or quantum mechanics concepts and constraints, including the differences between classical simulation, emulation, and hardware execution.
- Working knowledge of fundamental chemistry concepts and familiarity with molecular representations such as descriptors, fingerprints, molecular graphs, or SMILES.
- Strong interest in applying quantum computing to practical machine learning and scientific problems.
- Experience working with molecular, chemical, materials, or other scientific data.
- Ability to build end-to-end ML pipelines (pre/post-processing, integration with existing tools/platforms).
- Physics background (quantum/atomic/optics) is a plus.
- Delivery mindset and ownership (client-facing deliverables, pragmatism, trade-offs).
- Strong communication and collaboration with internal R&D, hardware, and platform teams.
Right to work in USA without sponsorship is preferred.
What we offer
- Flexible schedules to support work/life balance
- A dynamic, close-knit, collaborative, and diverse international team for co-workers
- An impactful role in a growing scale-up that is leading in the Neutral Atom Quantum Computing space
- Competitive benefit packages
- Lots of time off to enjoy the things you love outside of work
- Free time to learn and attend conferences/meetups
- Employment Terms : Full time, Direct hire, Hybrid
Recruitment process
- An interview with our talent acquisition team via Teams Video meeting
- A 1 hour video interview with hiring manager via Teams Video meeting
- For technical roles: A technical Interview round via Teams Video with the hiring manager
- Final Interview
- An offer !
PASQAL is an equal opportunity employer. We are committed to creating a diverse and inclusive workplace, as inclusion and diversity are essential to achieving our mission. We encourage applications from all qualified candidates, regardless of gender, music preference, ethnicity, age, religion or sexual orientation.
Department Software Role Quantum Application Locations Chicago Remote status Hybrid Employment type Full-time Seniority Senior