Open Position in Our Lab: Deep Learning for Structural Biology
We are inviting highly qualified undergraduate or graduate students to join our research group at the Oden Institute, University of Texas at Austin. This is a competitive opportunity for individuals with proven deep learning expertise and a strong interest in pioneering applications in computational biology.
About Our Work
Our lab is internationally recognized in molecular and structural modeling, with a focus on structure prediction. We are developing next-generation deep learning architectures that have outperformed models like AlphaFold3 and Boltz in benchmark evaluations. Our success has been validated in blind prediction challenges such as CASP16, CAPRI, and other international competitions. We integrate physical and biological insights with the latest advances in machine learning to accelerate drug discovery and tackle critical challenges in molecular biology. Our research is funded by CPRIT (Cancer Prevention and Research Institute of Texas), MD Anderson Cancer Center, and several leading pharmaceutical companies. These collaborations support ambitious, interdisciplinary projects with clear biomedical impact.
Ideal Candidate Profile
We are looking for individuals with:
- Strong experience in deep learning, especially in:
- Geometric Deep Learning
- Diffusion Models
- Related areas such as graph neural networks, equivariant architectures, and generative modeling
- Proficient programming skills and familiarity with modern machine learning frameworks
- Interest or background in biological or structural applications (preferred but not required)
Why Join Us
- Be part of a globally competitive lab at the forefront of AI and biology
- Contribute to projects with real-world applications in healthcare and drug design
- Collaborate with a multidisciplinary team of experts in computational biology, machine learning, and biophysics
- Gain hands-on experience in validating AI-driven discoveries through partnerships with experimental labs
We welcome motivated individuals eager to work in a dynamic and impactful research environment. If this aligns with your interests and background, we encourage you to apply by emailing ernestglukhov@my.utexas.edu (please also CC dima.kozakov@oden.utexas.edu).
