Postdoc: Physics-Informed ML for Porous Membrane Models

KAUST; Thuwal; On-site; SAR 180,000 - 240,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Housing on KAUST campus

Annual travel allowance

Paid vacation

Job summary

KAUST invites applications for a one-year postdoc position in the Inorganic Membranes Research Group. The role involves developing ML-accelerated physics simulations for membrane materials and collaborating with leading KAUST researchers, with competitive salary and benefits including housing on campus.

The successful candidate will have a PhD in relevant computational fields, strong publication record, and experience with Python, Julia, and scientific ML techniques.

Qualifications

• PhD in computational mathematics, computational mechanics, computational chemistry, machine/deep learning or closely related field.
• Candidate must have completed all PhD requirements by start and be within 5 years of completion.

Responsibilities

• Design and accelerate physics-based membrane simulations using ML methods.
• Collaborate with KAUST researchers in the Inorganic Membranes group to develop efficient models.

Skills

Python

Julia

Scientific machine learning

Deep learning

Computer vision

Code development

Education

PhD in computational mathematics/ computational mechanics/ computational chemistry/ machine/deep learning

Within 5 years of PhD completion

Tools

FEniCS

COMSOL

Ansys

Job description

KAUST invites applications for a one-year postdoc position in the Inorganic Membranes Research Group. The role involves developing ML-accelerated physics simulations for membrane materials and collaborating with leading KAUST researchers, with competitive salary and benefits including housing on campus.

The successful candidate will have a PhD in relevant computational fields, strong publication record, and experience with Python, Julia, and scientific ML techniques.