Computational Scientist

Role details

Job Title: Computational/AI Materials Scientist

Job Summary

As a Computational/AI Materials Scientist at Alsym Energy, you will help design the next generation of cathode and anode active materials powering safe and sustainable sodium-ion energy storage. You will join our Computational Materials Discovery team and work at the intersection of materials science, atomistic simulation and artificial intelligence. You will develop and apply advanced computational approaches to identify promising materials, understand their behavior, and guide experimental development.

We value scientific depth, creativity, and adaptability over expertise in any single methodology. We are looking for someone who can select and develop the right tools for challenging materials problems, whether through AI/ML, first-principles calculations, atomistic simulations, or new approaches.

Industry Background

Energy storage is one of the fastest-growing sectors in the global energy economy, with annual stationary storage capacity additions projected to grow 23% per year from 2025 to 2035, driven by surging electricity demand from electrification, data centers, and AI infrastructure. Alsym Energy is the leading developer of non-flammable, high-performance, low-cost sodium-ion batteries for AI data centers, utilities, commercial real estate and anywhere else energy storage is needed.

Key Qualifications

• Education: PhD in materials science, computational chemistry, condensed-matter physics, chemical engineering, computer science, or a closely related field.
• Core Technical Expertise: Demonstrated experience developing or applying computational methods such as AI/ML, first-principles calculations, or atomistic simulations to materials science problems.
• Domain Knowledge: Deep understanding of solid-state chemistry, electronic structure, thermodynamics, crystallography, and structure–property relationships.
• Collaboration: Track record of connecting in-silico predictions to experiments.
• Mindset: Scientific curiosity, initiative, adaptability, and enthusiasm for energy-materials discovery.

Preferred Qualifications

Advanced AI and ML:

• Agentic AI workflows and LLM applications for automated in-silico discovery.
• Generative AI for inverse materials design and crystal structure generation.
• Training, fine-tuning, and deploying machine learning interatomic potentials (MLIPs).
• Geometric and equivariant neural networks.
• Expertise in representation learning, descriptor engineering, and developing domain-specific materials representations.

Workflows:

• High-throughput calculation pipelines and automated workflow orchestration.
• Active-learning frameworks, Bayesian optimization, and uncertainty quantification for efficient candidate screening.
• Dataset curation and database management for multimodal data.

Materials Chemistry and Battery Science:

• Battery materials and electrochemistry.
• Predicting synthesizability, synthetic pathways, precursor selection, and processing conditions.
• Experience with the simulation of disordered and amorphous materials.
• Hands-on synthesis and characterization of solid-state materials.
• Multi-scale modeling bridging atomic-scale simulations to microstructure or device performance.

Roles & Responsibilities

• Drive computational projects to screen, optimize, and develop novel cathode and anode active materials for sodium-ion batteries, with a clear path to experimental evaluation.
• Develop and apply AI-driven methods, from ML-guided screening to automated discovery workflows, alongside first-principles calculations to accelerate materials design.
• Perform detailed computational analysis to evaluate the electrochemistry of materials during charge/discharge, providing insight into their performance, structural reversibility, and failure mechanisms.
• Partner directly with experimental synthesis, characterization, and cell-testing teams to design targeted experiments and benchmark computational predictions.
• Close the feedback loop by using experimental discrepancies to continuously refine models and translate findings into actionable materials design rules.
• Build reusable, well-documented computational infrastructure, codebases, and curated datasets while actively contributing to company IP.
• Take initiative and follow through – solve problems we didn’t know existed, or didn’t know could be solved.
• Present your work to the technical team, communicate it effectively to a broader audience, and share your knowledge and skills with colleagues.

Why Join Us?

At Alsym, we believe in equitable compensation and a healthy work-life balance. Beyond a competitive salary, we offer a benefits package designed to support you both inside and outside the office.

Perks & Lifestyle

• Prime Location: We are within easy walking distance of the train station.

• Commuter Friendly: Enjoy the convenience of free on-site parking.

• Health & Wellness: Stay active with access to our free on-site gym.

• Friday Fuel: We provide free lunch delivery every Friday to celebrate the end of the work week together.

Comprehensive Benefits

• Health & Dental: Premium insurance coverage through Blue Cross Blue Shield.

• Financial Future: Every employee is eligible for 401k plans and stock options.

• Time to Recharge: A flexible Paid Time Off (PTO) program to help you find your balance.

• Family & Security: Full eligibility for PFML (Paid Family and Medical Leave).

Our Commitment to You

We maintain a firm Anti-Harassment Policy that includes robust Diversity, Inclusion, Equity, and Gender Protections. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Note: A full, detailed listing of all benefits will be provided following a formal offer of employment.