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Introduction

IBM Research takes responsibility for technology and its role in society.

Working in IBM Research means you'll join a team who invent what's next in

computing, always choosing the big, urgent and mind-bending work that

endures and shapes generations. Our passion for discovery, and excitement

for defining the future of tech, is what builds our strong culture around

solving problems for clients and seeing the real world impact that you can

make.

IBM's product and technology landscape includes Research, Software, and

Infrastructure. Entering this domain positions you at the heart of IBM,

where growth and innovation thrive

Your role and responsibilities

We are seeking a motivated individual to develop/work on cutting-edge algorithms in math and science domains (e.g., physics, biology, or engineering) and translate them into scalable AI/ML models. The ideal candidate will bridge research and software development, collaborating with cross-functional teams to solve complex problems.

Key Responsibilities

* Design and implement algorithms for scientific or mathematical problems (e.g., optimization, simulation, data analysis).

* Develop and train AI/ML models (e.g., neural networks, NLP, computer vision) using Python and frameworks like PyTorch/TensorFlow.

* Translate research papers or theoretical concepts into production-ready code.

* Collaborate with researchers, data scientists, and engineers to integrate models into software systems.

* Document code, write unit tests, and maintain clean, modular software.

Required technical and professional expertise

* Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field.

* Published research experience (peer-reviewed papers in journals or conferences like NeurIPS, ICML, or domain-specific venues—preferably in PDEs, stochastic processes, or statistical modeling).

* Strong Python skills (e.g., NumPy, Pandas, Scikit-learn, and libraries for PDE solvers [e.g., FEniCS], stochastic simulations [e.g., PyMC3], or regression analysis [e.g., Statsmodels]).

* Proficiency in AI/ML model development (e.g., model training, evaluation, deployment).

* Basic software development skills: version control (Git), API design, cloud platforms (AWS/Azure/GCP), and software lifecycle principles.

* Strong foundation in mathematical modeling, including PDEs, stochastic processes, and linear regression.

Preferred:

* Experience with scientific computing libraries (e.g., SciPy, JAX, TensorFlow Probability).

* Familiarity with domain-specific tools (e.g., computational biology, quantum computing, or physics simulation).

* Open-source contributions or a GitHub portfolio demonstrating technical capabilities (e.g., PDE solvers, stochastic optimization, or regression-based AI models).

Preferred technical and professional experience

Hiring manager and Recruiter should collaborate to create the relevant verbiage.

IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.