ROLE DESCRIPTION:

We are looking for an innovative and driven researcher to join our interdisciplinary team working on cutting-edge projects, specifically focusing on Physics-Informed Neural Networks (PINNs). The successful candidate will leverage advanced mathematical modeling, deep physics knowledge, and deep learning methodologies to address complex physical challenges, optimize computational models, and advance the field of scientific computing.

JOB RESPONSIBILITIES:

• Develop, implement, and validate Physics-Informed Neural Networks (PINNs) for modeling and solving differential equations related to complex physical phenomena.
• Collaborate closely with domain experts to integrate physics constraints into neural network architectures.
• Conduct research aimed at improving the training efficiency, convergence, and accuracy of PINN models.
• Analyze, interpret, and visualize deep learning model outcomes, translating results into actionable insights.

REQUIREMENTS:

• Strong expertise in Deep Learning frameworks (e.g., PyTorch, TensorFlow).
• Solid understanding of theoretical physics, with the capability to derive and implement governing equations in neural network models.
• Proficiency in applied mathematics, particularly in partial differential equations (PDEs), numerical methods, and optimization techniques.
• Excellent programming skills in Python, particularly focused on deep learning and scientific computing.
• Experience developing and training Physics-Informed Neural Networks (PINNs) or similar models.
• Background or experience in Geophysics, especially seismic inversion, wave propagation, or related areas.
• Familiarity with numerical simulation tools and methods such as Finite Difference, Finite Element, or Spectral methods.
• Knowledge of probabilistic approaches, Bayesian methods, or uncertainty quantification in deep learning.
• Familiarity with MLOps practices and tools, including model versioning, continuous integration and deployment (CI/CD), experiment tracking, and containerization (e.g., Docker, Kubernetes).
• Curiosity-driven and innovative thinker who continually seeks improvements.
• Strong communication skills, particularly the ability to clearly explain complex concepts to interdisciplinary teams.
• Highly motivated and capable of independent and collaborative work in a research-focused environment.
• Practical mindset with a focus on delivering tangible results and real-world applications.

HIRING TERMS:

• Full-time job
• Five-days working week
• Flexible working hours
• Medical insurance package (family cover)
• Push 30 (Wellness Program)
• Company-provided lunch

Interested candidates can apply via the link in the Apply for job button.

• Bizi izləyin:
• 
• 
• 
• 
•