Assistant Professor - Artificial Intelligence / Machine Learning

University of Texas Medical Branch-posted 3 months ago
Entry Level
Galveston, TX
5,001-10,000 employees
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The newly established Sealy Institute for Drug Discovery seeks an outstanding bioinformatics expert for a tenure-track position at the rank of Assistant Professor at the University of Texas Medical Branch (UTMB), Galveston, Texas. Applicants meeting criteria for higher ranks will also be considered. The candidate is expected to have skills such as a PhD in Computer Science, Bioinformatics, Computational Biology, or a related field, with a strong emphasis on AI and machine learning. The position offers an opportunity to work in a highly collaborative environment with access to outstanding research facilities and resources.

  • PhD in Computer Science, Bioinformatics, Computational Biology, or a related field, with a strong emphasis on AI and machine learning.
  • Postdoctoral or equivalent experience.
  • A proven track record of research in applying AI to biological or chemical datasets with publications in peer-reviewed journals.
  • Demonstrated ability to handle large (Big Data) datasets and experience with computational tools and databases relevant to genomics, proteomics, and drug discovery.
  • Knowledge of biological and chemical data formats and standards, such as FASTA, FASTQ, BAM, VCF, BED, GFF, PDB, and SDF.
  • Excellent communication and presentation skills, both oral and written.
  • Strong problem-solving and critical thinking skills.
  • Ability to work independently and collaboratively in a multidisciplinary and dynamic environment.
  • High motivation and passion for bioinformatics and biomedical research.
  • Strong theoretical understanding of key frameworks and AI model architectures.
  • Proficiency in Python and R as well as key frameworks for AI development (e.g. PyTorch, TensorFlow, JAX or equivalent).
  • Familiarity with pipeline development and ability to work with teams to scale and operationalize new models and training regimes.
  • Deep expertise in AI model development and an ability to extend and apply tools such as AlphaFold, DiffDock, MolBert and similar tools in new and creative ways.
  • Expertise in current model and paradigms such as transformers, graph neural networks, and embeddings.
  • Access to outstanding research facilities for next-generation sequencing, mass spectrometry, optical microscopy, flow cytometry, solution biophysics, NMR, X-ray crystallography, cryo-electron microscopy, scientific computing, bioinformatics and deep computational resources.
  • Excellent opportunities for scientific interactions through sister institutions in the Texas Medical Center and greater Houston area, Gulf Coast Consortia, and the Keck Center for Interdisciplinary Bioscience.
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