At a Glance
- Tasks: Develop and validate models for materials and processes in a cutting-edge AI environment.
- Company: Join a pioneering company transforming the materials industry with innovative technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative team culture with exciting challenges and career advancement.
- Why this job: Make a real impact on sustainability and efficiency in the materials sector.
- Qualifications: Strong background in chemical and process engineering, with Python skills.
The predicted salary is between 45000 - 55000 £ per year.
Everything physical is made from raw materials: polymers, chemicals, metals and minerals, a $16T economy that software has barely modelled. Atmospheric AI computes what those materials should cost, what carbon they carry and where their supply is exposed, from the physics of how they're made, so manufacturers can decide and negotiate from ground truth.
The problem
Our cost, carbon and substitution answers are computed from process and material models. A buyer asking whether one grade can replace another, or what a converter's energy bill does to its price, is asking those models a question. They have to respect mass and energy balances, connect grades to the technologies that make them, and say plainly where they stop being valid. Physics has the final say, and you'll have the authority to block a release when the evidence doesn't hold.
What you'll own
- Transformation models. Industrial processes with credible mass and energy balances, yields, utilities and by-products, within thermodynamic and reaction-engineering constraints.
- Conversion models. How materials become intermediate and finished products: extrusion, moulding, film and fibre, forming and finishing.
- The material layer. Grade comparison, substitutability, and which technologies and units could have made a given grade.
- Canonical scientific tables. Shared identifiers, classifications and hierarchies for materials, chemicals, properties, grades and processes, so the whole product speaks one scientific language.
- Validation as tests. Benchmarks against simulation, licensor, literature and plant evidence, with physical constraints turned into automated tests.
- The quality bar. Models with stated coverage, uncertainty and limits. Nothing ships that fails the physics.
What we're looking for
- Strong chemical and process-engineering fundamentals: mass and energy balances, thermodynamics, reaction engineering, separations, process economics, unit operations.
- Materials knowledge. How composition, structure and production technology set grade properties and substitutability.
- A validation mindset. You design tests that could prove your model wrong, set tolerances and withhold approval when the evidence is thin.
- Strong Python modelling. Modular, tested, reproducible code someone else can review and maintain, and the data-modelling sense to keep canonical tables durable.
- Depth in one family, reach beyond it. You can carry your reasoning into metals, paper, fibres or new chemical systems.
Nice signals: Aspen Plus, HYSYS or comparable simulation; technical datasheets, grade databases or licensor data; taking a scientific model into production yourself; Databricks and MLflow or equivalent; a Master's or PhD in chemical, process or materials engineering or polymer science.
Stack: Python, FastAPI, Postgres, Dagster, AWS. A signal, never a requirement.
The take-home: we send you a small transformation model with one physical error in it. Find it, write the tests that would have caught it, and propose the fix.
Materials & Process Scientist in London employer: Atmospheric AI
Atmospheric AI provides a collaborative work environment where employees can engage in meaningful projects that address critical environmental challenges. The company emphasizes professional growth and offers opportunities to work with innovative technologies in the field of data science. Employees are part of a team that contributes to impactful solutions in the materials economy.
StudySmarter Expert Advice🤫
We think this is how you could land Materials & Process Scientist in London
✨Join Engineering Meetups!
Get yourself along to local engineering meetups or tech conferences. These are great places to connect with like-minded folks and industry leaders who might just have a lead on that full-time Materials & Process Scientist role you’re after at Atmospheric AI.
✨Show Off Your Projects!
Don’t be shy about showcasing your engineering projects. Whether it’s a funky app, a mechanical design, or a complex algorithm, having a solid portfolio on platforms like GitHub can really make you stand out. Plus, it gives potential employers at Atmospheric AI a taste of what you can bring to the table!
✨Engage with Online Communities
Dive into engineering forums and online communities, like Reddit or specific engineering Discord channels. Sharing your insights, asking questions, and being active can help you build connections that might lead to job opportunities at Atmospheric AI.
✨Apply Through Company Websites
When you spot a role like Materials & Process Scientist at Atmospheric AI, apply directly through their website. Often, this can show your genuine interest in the company and you might just get noticed quicker than via typical job boards.
We think you need these skills to ace Materials & Process Scientist in London
Some tips for your application 🫡
Showcase Your Technical Expertise:When applying for an engineering role like Materials & Process Scientist, it’s essential to highlight your technical skills. Include any relevant software or tools you're proficient in on your CV—think CAD software, simulation tools, or programming languages. Don't skimp on any engineering projects you've worked on that demonstrate your ability to solve complex problems.
Focus on Results and Impact:In the engineering world, we love numbers and real-world impact. Quantify your achievements wherever possible—like reducing costs by a certain percentage, improving efficiency, or successfully completing a project ahead of schedule. This gives your future employers at Atmospheric AI a clear picture of the value you can bring.
Craft a Compelling Cover Letter:Use your cover letter to express your passion for engineering and explain why you’re drawn to Atmospheric AI specifically. Share what aspects of their work excite you and how your values align with theirs. This is your chance to show a bit of personality while keeping it professional!
Include Relevant Certifications:If you have any engineering certifications, especially ones that are recognised in your field, make sure to feature them prominently on your CV. They demonstrate not just your knowledge, but also your commitment to professional development, which is something we at StudySmarter value highly.
How to prepare for a job interview at Atmospheric AI
✨Brush Up on Core Engineering Principles
Before heading into the interview with Atmospheric AI, make sure you're solid on the fundamental engineering principles relevant to the role. Be ready to discuss concepts such as thermodynamics, fluid mechanics, or structural analysis, depending on the specifics mentioned in the job description. Don’t skip any hands-on projects or coursework; these can be excellent talking points!
✨Show Off Your Problem-Solving Skills
Expect technical questions or case studies during your interview—after all, engineering is all about solving problems! Prepare a few examples of how you've tackled engineering challenges in the past, whether at university or in any practical experience. Practising with mock technical interviews can really help you articulate your thought process and solutions.
✨Relate Your Experience to the Role
In a full-time role, employers like Atmospheric AI want to see that you can adapt and grow within their team. Be ready to discuss how your previous internships, projects, or studies relate directly to the work you'll be doing. Highlight specific experiences that showcase your collaborative skills and how you've successfully worked within a team environment.
✨Know Your Tools and Software
Most engineering roles require familiarity with specific tools and software. Prepare to talk about your proficiency with programmes like AutoCAD, MATLAB, or SolidWorks if they’re relevant to the role. Even better, have examples of projects where you’ve used these tools, as it'll demonstrate your hands-on experience and readiness for the job.
