Computational Material Scientist

Job Description

We are seeking a Computational Materials Scientist to join our Applied Metrology Team.

The AM team (i) leads technical interactions with customers, prospects and stakeholders, including in-house demonstration studies, and the delivery and installation of SirenOpt’s PlasmaSens products at customer sites and (ii) uses such interactions to inform and perform R&D to improve the performance of SirenOpt’s metrology and manufacturing intelligence platforms. The AM team also provides consultation, training and support services to customers.

A key aspect of the Computational Materials Scientist role is to advise the machine learning team on the development of new learning-based strategies (e.g., physics-informed machine learning models, optimization-based decision-making algorithms) to transform the metrology platform’s complex raw data into actionable insights for customers, material property and performance quantifications, and suggested/automated actions by customers (e.g., automated process tuning and real-time process control). This role will also investigate new data-driven and physics-informed ways of featurizing the metrology platform’s raw data to inform the learning-based strategies mentioned above.

If you are a driven and skilled computational materials scientist looking to make a significant impact in advanced manufacturing and the green energy transition, we encourage you to apply.

We believe that the most innovative teams are inclusive and celebrate all forms of diversity. We highly encourage candidates from unrepresented groups to apply.

In this role you will:

• Develop, investigate, and validate learning-based strategies to transform the metrology platform’s complex raw data into actionable insights for customers, material property and performance quantifications, and suggested/automated actions by customers

• Implement the learning-based strategies mentioned above directly into SirenOpt’s software stack and validate their performance within that stack

• Investigate the metrology platform’s raw data to determine physics-based relationships between the raw data and relevant quantifications, classifications, and decisions for customers

• investigate new data-driven and physics-informed ways of featurizing the metrology platform’s raw data to inform the learning-based strategies mentioned above

• Work closely with customers, prospects and collaborators to understand their material and product metrology requirements, and use that understanding to define and execute on demonstration studies and proof-of-concept efforts

• Report and discuss demo study results with customers, and utilize their feedback to provide direction on next steps both internally and externally

• Demonstrate SirenOpt’s solutions and technology to customers and stakeholders during customer visits, as well as at both in-person and virtual events and conferences

• Provide feedback to the SirenOpt product and engineering teams on user experience in order to improve customer satisfaction.

• Identify new applications, performance capabilities, product features and value to further enhance SirenOpt product and market opportunities

• Work closely with your colleagues in the Applied Metrology  team to create & improve new methodologies and process to optimize both internal and external platform performance

• Perform concept and feasibility, and qualification analyses of new metrology approaches

• Document platform/product best practices and procedures for external stakeholders and colleagues

You have:

• A Master’s or PhD in a relevant engineering or technical discipline, including chemical engineering, materials science, chemistry, physics, or a related discipline
• 1-5 years' work experience related to manufacturing, metrology, characterization and/or materials development, preferably with thin films and/or their precursor materials
• Previous experience working with hardware, software and/or analytics products that target manufacturing sectors
• Solid understanding of machine learning and data science, especially as it relates to industrial applications for ML, and experience with data analysis tools (e.g., Matlab), languages (e.g., Python), and machine learning toolboxes (e.g., PyTorch). Experience with advanced methods for dimensionality reduction, probabilistic modeling, Bayesian Optimization, optimal experiment design, and sensitivity analyses is a plus.
• Strong people skills, and a demonstrated ability to work closely with both internal and external stakeholders to deliver results
• Travel to global customer sites, conferences and trade shows will be required, so possession of a valid passport and the willingness to use it will be required
• Excellent written and verbal communication skills
• Demonstrated ability to adapt to new challenges and excited to work in a fast-paced, multi-disciplinary environment
• The ideal candidate will learn new concepts quickly and take pride in the quality of their work. 
• Curiosity, a self-starting attitude and a desire to see your work positively impact manufacturing across industries and across the globe