Role Overview: We are seeking a Machine Learning Researcher with a strong background in machine learning and data science, with a focus on applying these skills to materials science. The ideal candidate will excel in developing and optimizing machine learning models, including Bayesian optimization and active learning strategies, to predict material properties, accelerate simulations, and solve complex problems in materials design.

Desired Skills and Qualifications:

Education & Experience:

Field: Data Science/Machine Learning, Computer Science, or a related field.
Experience: Ph.D. in a relevant field with research experience in developing new machine learning methodologies or a Master’s degree with 3-5 years of research-oriented experience in ML development.
Candidates with Computational Material Science or Alloy Design related experience will be preferred.

Technical Skills:

Expertise in developing and implementing machine learning algorithms, including but not limited to deep learning, gaussian processes, generative modelling, graph neural networks, Bayesian optimization, and active learning.
Proficiency in Python and Machine Learning frameworks (e.g., TensorFlow, PyTorch).
Proficiency in Linux-based command line tools.
Familiarity with data science and machine learning packages.
Nice to have: Experience with computational materials science libraries (e.g., matminer, pymatgen, etc).

Domain Knowledge:

Strong foundation in machine learning, with a focus on developing new methodologies and algorithms.
A basic understanding of materials science principles is a plus.

Key Responsibilities:

Algorithm Development:

Research and develop novel machine learning algorithms tailored to the unique challenges of materials design.
Lead projects focused on creating state-of-the-art models for the inverse design of new materials and predicting material properties.
Innovate new methods for accelerating computational materials simulations through advanced machine learning techniques.
Establish and maintain feedback loops to iteratively improve models and methodologies.

Optimization:

Design and implement Bayesian optimization strategies for multi-objective optimization in materials design.
Develop and apply active learning frameworks to optimize data generation and enhance model precision and efficiency.

Software Development:

Develop and maintain tools that integrate machine learning with computational materials science workflows.
Experience with high-performance computing and cloud environments (AWS, Azure, Google Cloud) is a plus.
Nice to have: Experience with MLOps and workflow orchestration.

Collaboration & Leadership:

Work closely with cross-functional teams, including materials scientists and engineers, to translate machine learning research into real-world applications.
Mentor junior researchers and team members, guiding them in developing machine learning techniques and their applications.
Lead initiatives to identify and implement process improvements across the company’s research and development efforts.

What We Offer:

Competitive salary and benefits package.
Opportunity to work with a leading advanced materials company.
Collaborative and dynamic work environment.
Professional development opportunities and career growth.
Relocation support for the right candidate.

Benefits:

Competitive Compensation Package: Attractive salary with stock options, giving you a share in our success.
Health Benefits: Comprehensive health care plan that includes Medical, Dental, Vision, and Mental Health support, ensuring a holistic approach to health and well-being.
Paid Time Off: Generous leave policies include vacation, sick days, and public holidays, promoting work-life balance.
Professional Development: Dedicated budgets for skill enhancement, including conferences, workshops, and additional training tailored to your interests and career goals.
Flexible Working Conditions: Remote work options and flexible hours to accommodate your lifestyle and increase productivity.
Innovative Culture: Join a team that values innovation and is open to ideas that challenge the norm.
Dynamic Environment: Fast-paced and agile workplace that allows you to see the impact of your work directly and quickly.
Access to Cutting-Edge Technology: Work with the latest technologies and tools in materials science and computational modelling.
Collaborative Atmosphere: Close collaboration with a small, passionate team allows for hands-on contributions to projects that make a difference.
Sense of Ownership: Take ownership of your projects with the opportunity to grow into decision-making roles as you demonstrate your capabilities and help shape the company's future.

Join Us: If you're passionate about pushing the boundaries of materials engineering and enjoy working in a dynamic environment to solve complex problems that have the potential to create real-world impact, apply now to help us drive the future of material science.

How to Apply: Interested candidates are invited to submit their resume and cover letter outlining their qualifications and experience to hiring@thephaseshift.com. Please include "Application for Machine Learning Researcher" in the subject line. If you have already submitted your application for "Materials Informatics Engineer" role, we are already considering it as part of this role.

Deadline: September 15th, 2024. Please note that if a candidate is identified before the deadline, the job opening may be closed earlier than the posted date.

About PhaseShift Technologies Inc.: PhaseShift is advancing the materials industry by designing and commercializing new and innovative engineering materials, including alloys and ceramics. Our proprietary computational materials engineering platform leverages AI to rapidly design and optimize new materials, fundamentally accelerating the pace of innovation in the materials industry. This streamlined approach significantly reduces R&D time and costs, allowing us to explore a broader range of opportunities than traditional methods allow.

The materials we develop play a crucial role in addressing key technological and sustainability challenges across various industries, from aerospace to energy. By accelerating the development of new materials, our work supports industry advancements that lead to products and solutions that are better performing, more efficient, more cost-effective, and more sustainable.

We believe in our technology, which is why we use it internally to develop our own materials. Our commercial strategy involves collaborating with manufacturers and licensing our innovation to ensure these novel materials reach the market effectively, maximizing their impact.

PhaseShift Technologies Inc. is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Phaseshift Technologies

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