About the Role

We are seeking aSenior Technical Officer (博士级高级技术官) to drive our computational discovery platform at the intersection of materials physics, molecular simulation, and artificial intelligence. You will lead first-principles and coarse-grained modelling efforts to accelerate the design of novel biosensor interfaces, plasmonic nanostructures, and diagnostic assay architectures. This role combines deep scientific computing with modern AI/ML pipelines, all executed on institutional HPC infrastructure spanning the Greater Bay Area.

Key Responsibilities

1. Computational Materials & Biophysics– Perform ab initio electronic-structure calculations (Quantum Espresso), excited-state/plasmonic response modelling (Yambo), and classical molecular-dynamics simulations (Gromacs) to guide materials selection and surface-functionalisation strategies.
2. Photonic & Electromagnetic Simulation– Design and optimise nanophotonic components (e.g., LSPR waveguides, microfluidic-integrated optical polarisers) using MEEP(FDTD) and related computational electrodynamics tools.
3. HPC Infrastructure Stewardship – Administer and optimise our High-Performance Cluster environments (Slurm scheduling, MPI/OpenMP tuning, storage hierarchy, conda/containerised software stacks) to ensure secure, multi-user execution of large-scale DFT and MD workloads (preferred).
4. AI-Driven Discovery – Develop and deploy deep-learning models (CNN, RNN, Transformer, LLM) for surrogate modelling of DFT energies, generative design of molecular candidates, or automated analysis of simulation trajectories and patent literature (preferred).
5. Intellectual Property–Draft patent application documents(invention disclosures, PCT/CN claims, technical drawings) in both Chinese and English; translate complex simulation results into defensible IP assets.
6. Cross-Border R&D Collaboration– Communicate fluently in Chinese and English during joint projects with Greater Bay Area partners; travel regularly between Shenzhen and Hong Kong for cluster access, and technical reviews.

Requirements

Must-Have

• PhD in Physics, Chemistry, Materials Science, Bioinformatics, or related quantitative discipline
• Fresh grad. PhD or equivalent industrial/academic R&D in computational materials/biophysics
• Expert-level proficiency in Quantum Espresso and at least one of Yambo / Gromacs / MEEP
• Solid programming foundation in Python/C++ for scientific computing and workflow automation
• Bilingual professional fluency (Chinese & English) for technical writing and oral presentation

Preferred (Highly Valued)

• Demonstrated experience in HPC cluster administration (Slurm; Linux sysadmin; Infiniband/GPU node management)
• Proven track record applying AI/ML architectures (CNN, RNN, Transformer, LLM) to scientific datasets or simulation outputs
• Prior filing of ≥2 invention patents as principal or co-inventor
• Experience with container technologies (Singularity/Apptainer, Docker) and CI/CD for reproducible simulation pipelines
• Familiarity with biotech/biosensor commercialisation and IVD regulatory data packages

We Offer

• Competitive compensation aligned with doctoral expertise, HPC stewardship scope, and patent output.
• Direct ownership of a multi-physics simulation platform interfacing with wet-lab microfluidics and LSPR hardware biosensor teams.
• Opportunity to build a joint IP portfolio spanning computational materials design and AI-assisted diagnostics.
• Greater Bay Area ecosystem access, including collaboration with Hong Kong–Shenzhen supercomputing centres and university beam lines.

How to Apply

Please submit your CV, publication list, and a brief technical portfolio (GitHub repositories, HPC architecture diagrams, or AI model demo cases) to admin@rafaelbiotech.com
Shortlisted candidates will be invited for a technical seminar (in English or Chinese) in Shenzhen or Hong Kong within two weeks.

To work with 3D printing equipment and sample preparation. Candidate with BSc/BEng degree is preferred and shall be able to work independently and report to duty on time. Good communication in English and Chinese.