Join the Cablab Team

Let's work to drive innovation at the intersection of AI and materials science

We're always looking for talent and passion to us in our mission to individuals to join our mission of accelerating scientific discovery at the intersection of AI, materials science, and bioinformatics.

Our lab offers the excitement of elucidating the fundamental physics of the universe and our complex biology with all of the modern benefit in-silico work.

If the prospect of providing novel algorithms to the scientific community while working in a computational environment with optional collaboration in traditional wet-lab spaces sounds appealing, or if you are interested in any of our research areas, then please reach out via email and we can set up a meeting to discuss next steps.

What We Offer

  • Cutting-edge Research: Our intersection of AI, nanomaterials, and bioinformatics offers a unique research perspective with high prospects for novelty
  • Interdisciplinary Environment: Our lab in Materials Science and Engineering at UCF fosters collaboration with experts in quantum physics, computer science, nanotheranostics, systems biology, and materials engineering
  • State-of-the-art Resources: Access to UCF, cloud-provider, and cablab on-site GPU high-performance computing (HPC) clusters
  • Professional Development: Regular academic conferences, hackathons & hacking conferences, industry connections, academic puclishing, and mentorship throughout it all
  • Supportive Culture: Ideas and their translation to code are important. We believe great ideas can come from anyone, regardless of their background, embrace all UCF policies, and hope to foster a diverse and inclusive research environment.

Open Positions

We're seeking candidates in all positions (PhD candidates / graduate students, postdoctoral researchers, and undergraduates).

Desired Interests:

  • Developing novel AI architectures for materials property prediction
  • Laboratory automation
  • Creating automated platforms for biological data analysis
  • Designing new computational methods for drug discovery
  • Applying machine learning to experimental design optimization
  • Automated high-throughput experimentation systems
  • Quantum computing applications in materials science
  • Decentralized and reproducible build systems

Desired skills:

  • Languages: Python, Julia, Typst, LaTeX, Rust, C, C++
  • Reproducible science tech: iroh, nix, git, slurm, docker/podman
  • DFT & QM software: Yambo, BerkleyGW, VASP, QuantumEspresso

PhD Students

Requirements:

  • MSc/BS in Computer Science, Materials Science, Bioinformatics, or related field
  • Programming experience
  • Background in machine learning or eagerness to learn
  • Communication & collaboration skills

Postdoctoral Researchers

Requirements:

  • PhD in relevant field
  • Publication track record
  • Experience with AI/ML frameworks
  • Project leadership abilities

Undergraduate Researchers

Requirements:

  • Current enrollment in related major
  • Basic programming knowledge
  • Strong interest in AI and scientific research

How to Apply

  1. PhD | MSc | Postdoc:

    • Email your CV (optionally: resumé for PhD), research statement, and three references.
    • Subject line: "{PhD|Msc|Postdoc} Application: $YourName"

  2. Undergraduate:

    • Send your transcript, resumé, and brief statement of interest to the email address for cablab
    • Include any relevant project experience or coursework