Qureos Mentor

Lila Sciences

<div>
 
 
 🚀&nbsp;About Lila Sciences
 
 
 
 Lila Sciences is the world&rsquo;s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai  &nbsp;&nbsp;
 
 
 At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.
 
 
 If this sounds like an environment you&rsquo;d love to work in, even if you only have some of the experience listed below, please apply.
 
 
 
 🌟&nbsp;Your Impact at Lila
 
 
 
 As a Research Scientist on our Physical Sciences team, you will lead the development of automated, high-throughput workflows for the synthesis and discovery of porous materials. You&rsquo;ll design experimental pipelines to synthesize and characterize diverse classes of porous materials such as MOFs, zeolitic materials, metal oxides and more. Your work will accelerate closed-loop experimentation and AI-guided materials discovery, helping us unlock new frontiers in separations, catalysis, and clean energy technologies.
 
 
 
 🛠️&nbsp;What You'll Be Building
 
 
 <ul>
 <li>
 Design &amp; develop automated synthesis workflows for porous materials across multiple classes and synthetic routes (e.g., solvothermal, hydrothermal, ionothermal).
 </li>
 <li>
 Partner with engineering team to build, operate, and optimize robotic platforms and parallel synthesis systems for high-throughput experimentation.
 </li>
 <li>
 Partner with engineering team to interface hardware systems (reactors, sensors, analytics) with software pipelines for metadata capture, scheduling, and orchestration.
 </li>
 <li>
 Partner with AI teams to enable closed-loop experimentation and iterative hypothesis generation.
 </li>
 <li>
 Collaborate across materials science, engineering, and data science teams to drive platform development, documentation, and discovery.
 </li>
 </ul>
 
 
 🧰&nbsp;What You&rsquo;ll Need to Succeed
 
 
 <ul>
 <li>
 PhD. or M.S. in Chemistry, Chemical Engineering, Materials Science, or related field.
 </li>
 <li>
 &ge; 5 years of experience in synthesis and characterization of porous materials (e.g., MOFs, zeolites, oxides etc).
 </li>
 <li>
 Strong track record with robotic synthesis platforms, high-throughput experimentation, or automated materials discovery.
 </li>
 <li>
 Proficiency in Python for instrument scripting, workflow development, and data handling.
 </li>
 <li>
 Deep knowledge of synthetic methodologies and solid-state or solution-phase chemistry.
 </li>
 </ul>
 
 
 ✨&nbsp;Bonus Points For
 
 
 <ul>
 <li>
 Experience with commercial automation platforms (e.g., Chemspeed, Hamilton, Tecan) or custom-built robotic systems.
 </li>
 <li>
 Familiarity with in situ or high-throughput characterization methods (e.g., PXRD, adsorption, TGA etc).
 </li>
 <li>
 Prior work in self-driving labs or AI-guided discovery loops.
 </li>
 <li>
 Comfort with cloud-based orchestration and scientific software stack integration.
 </li>
 <li>
 Contributions to open-source or community-driven lab automation tools.
 </li>
 </ul>
 
 
 🌈 We&rsquo;re All In
 
 
 
 Lila Sciences is&nbsp;
 
 committed to equal employment opportunity
 
 regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
 
 
 
 🤝&nbsp;A Note to Agencies
 
 
 
 
 
 
 Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science&rsquo;s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
 
 
</div>

Research Scientist, Automated Synthesis

<div>
 
 
 🚀&nbsp;About Lila Sciences
 
 
 
 Lila Sciences is the world&rsquo;s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai  &nbsp;&nbsp;
 
 
 At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.
 
 
 If this sounds like an environment you&rsquo;d love to work in, even if you only have some of the experience listed below, please apply.
 
 
 
 🌟&nbsp;Your Impact at Lila
 
 
 
 As a Scientist/Senior Scientist on our Physical Sciences team, you will design advanced synthesis platforms for the synthesis and characterization of zeolitic materials. Your work will be enabling high-throughput experimentation integrated with real-time analytics. Collaborating across chemistry, material science, machine learning, and data science teams, you&rsquo;ll help establish next-generation tools for advanced porous material development platforms.
 
 
 
 🛠️&nbsp;What You'll Be Building
 
 
 <ul>
 <li>
 
 Design &amp; Commission:
 
 Design and validate systems for synthesis of zeolitic and other types of porous materials with the help of our automation engineering team.
 </li>
 <li>
 
 Integrate &amp; Scale:
 
 Interface near real-time high throughput characterization tools with platforms to enable feedback-driven synthesis and formulation.
 </li>
 <li>
 
 Workflow Optimization:
 
 Integrate the synthesis platforms with robotics and software pipelines for automated high-throughput experimentation and data-rich workflows.
 </li>
 <li>
 
 Closed-Loop Execution:
 
 Collaborate with AI teams to run iterative experiments in real time, enabling fast optimization and discovery cycles.
 </li>
 <li>
 
 Collaboration &amp; Documentation:
 
 Work with chemists, material scientists, engineers, and data scientists to document systems, share insights, and refine best practices in autonomous porous material chemistry.
 </li>
 </ul>
 
 
 🧰&nbsp;What You&rsquo;ll Need to Succeed
 
 
 <ul>
 <li>
 Ph.D. or M.S. in Chemistry, Chemical Engineering, Material Science or a related field.
 </li>
 <li>
 &ge; 5 years of hands-on experience in zeolitic material synthesis.
 </li>
 <li>
 Deep expertise in porous material characterization
 </li>
 <li>
 Experience in integrating analytical instruments into automated or modular experimentation platforms.
 </li>
 <li>
 Experience in high throughput synthesis and characterization techniques.
 </li>
 <li>
 Excellent troubleshooting, communication, and interdisciplinary collaboration skills; ability to both innovate and communicate cross-functionally across materials science domains.
 </li>
 <li>
 Experience in powder x-ray diffraction technique and data analysis (indexing, and refinement)
 </li>
 </ul>
 
 
 ✨&nbsp;Bonus Points For
 
 
 <ul>
 <li>
 Proficiency in Python or other scripting languages for data analysis.
 </li>
 <li>
 Experience with self-driving lab platforms or closed-loop optimization systems.
 </li>
 <li>
 Knowledge of design-of-experiment (DoE) methods and Bayesian optimization.
 </li>
 <li>
 Experience contributing to scientific software tools or open-source automation frameworks.
 </li>
 </ul>
 
 
 🌈 We&rsquo;re All In
 
 
 
 Lila Sciences is&nbsp;
 
 committed to equal employment opportunity
 
 regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
 
 
 
 🤝&nbsp;A Note to Agencies
 
 
 
 
 
 
 Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science&rsquo;s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
 
 
</div>

Research Scientist, Porous Materials

<div>
 
 
 🚀&nbsp;About Lila Sciences
 
 
 
 Lila Sciences is the world&rsquo;s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science.  We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method.  We are introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at  www.lila.ai  &nbsp;&nbsp;
 
 
 At Lila, we are uniquely cross-functional and collaborative. We are actively reimagining the way teams work together and communicate. Therefore, we seek individuals with an inclusive mindset and a diversity of thought. Our teams thrive in unstructured and creative environments. All voices are heard because we know that experience comes in many forms, skills are transferable, and passion goes a long way.
 
 
 If this sounds like an environment you&rsquo;d love to work in, even if you only have some of the experience listed below, please apply.
 
 
 
 🌟&nbsp;Your Impact at Lila
 
 
 
 Your role in our Physical Sciences division will focus on developing and adapting state-of-the-art interatomic potentials for diverse material systems, integrating them into agentic AI frameworks, and connecting atomistic simulations to automated labs to drive materials discovery. Your work will play a key role in unlocking the potential of simulations towards autonomous and intelligent scientific discovery. You will partner with diverse teams at Lila, including machine learning experts working on scientific superintelligence and materials science experts performing real-world experiments.
 
 
 
 🛠️&nbsp;What You'll Be Building
 
 
 <ul>
 <li>
 Develop, fine-tune, and deploy physics-informed interatomic potentials across crystalline, amorphous, and multi-component materials systems.
 </li>
 <li>
 Develop infrastructure for integrating interatomic potentials into scalable agentic frameworks for autonomous materials design and discovery.
 </li>
 <li>
 Collaborate with automation scientists to link simulations with high-throughput lab experiments.
 </li>
 <li>
 Partner with materials scientists, AI researchers, and platform engineers to deploy scalable simulation workflows for scientific discovery.
 </li>
 </ul>
 
 
 🧰&nbsp;What You&rsquo;ll Need to Succeed
 
 
 <ul>
 <li>
 PhD or equivalent research/industry experience in Computational Materials Science, Computational Chemistry, Computer Science, Machine Learning, or related fields.
 </li>
 <li>
 Strong programming skills and expertise in machine learning frameworks (PyTorch, JAX, etc.)
 </li>
 <li>
 Expertise in working with machine learned interatomic potentials, including but not limited to model architecture, fine-tuning, distillation, or workflow development
 </li>
 <li>
 Demonstrated track record in developing robust, reproducible code for interatomic potentials and frameworks
 </li>
 <li>
 Experience in running molecular dynamics simulations and frameworks (LAMMPS, OpenMM, etc.)
 </li>
 <li>
 Familiarity with deploying models and workflows on HPC and cloud-based computing resources at scale
 </li>
 </ul>
 
 
 ✨&nbsp;Bonus Points For
 
 
 <ul>
 <li>
 Strong publication record in developing and applying interatomic potentials for applications in the chemical and materials sciences, with a focus on inorganic materials
 </li>
 <li>
 Experience in&nbsp;working with LLM models and frameworks (HuggingFace Transformers, ****LangChain, Pydantic, and related toolkits).
 </li>
 <li>
 Prior work in developing agentic frameworks for atomistic simulations and/or autonomous materials discovery pipelines
 </li>
 </ul>
 
 
 🌈 We&rsquo;re All In
 
 
 
 Lila Sciences is&nbsp;
 
 committed to equal employment opportunity
 
 regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
 
 
 
 🤝&nbsp;A Note to Agencies
 
 
 
 
 
 
 Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science&rsquo;s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
 
 
</div>

ML Research Scientist, Interatomic Potentials

Join Lila Sciences and explore 3   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Lila Sciences

ABOUT_COMPANY

Research Scientist, Automated Synthesis

Research Scientist, Porous Materials

ML Research Scientist, Interatomic Potentials