Postdoctoral Fellow, Dr. Talmo Preira

  • Salk Institute for Biological Studies
  • La Jolla, CA 920371002, USA
  • Oct 13, 2021
Full time Biology/Biotechnology/Life Sciences

Job Description

We have multiple post-doctoral positions available for computational researchers in Talmo Pereira's lab. Our work leverages computer vision and deep learning to solve biological problems across diverse application areas, including neuroscience, plant biology and cell biology. We are looking for candidates with a strong background in computational work and looking to work closely with experimentalists to develop and apply machine learning models to tackle biological problems.

Potential project areas and associated approaches include:

  • Movement phenotyping: pose estimation, multi-animal tracking, behavior segmentation/action recognition
  • âPlant phenotyping: shape estimation, image segmentation, multi-view reconstruction
  • Artificial neural network-based modeling: agent-based models, imitation learning, interpretable AI, generative sequence models, probabilistic programming

Specific projects will involve collaboration with experimental labs working on motor control, social behaviors, plant biosynthesis pathway engineering to tackle climate change and more. Data will come from a variety of model species (flies, mice, plants) and collaborators (e.g., Tye Lab, Azim Lab, Asahina Lab, Manor Lab, Busch Lab, Behavioral Testing Core, and more).


  • Work with experimentalists to guide study designâ and data collection to optimize for computational pipelines.
  • Develop and/or apply data analysis pipelines using state-of-the-art deep learning-based systems.
  • Describe scientific findings and methods in conference proceedings and journal publications.â
  • Work with and mentor trainees at all levels, including collaborators.
  • (Project-dependent) Work with software engineers to build and distribute software tools, as well as interact with communities of practitioners to set new standards and protocols for analysis and modeling.
  • (Project-dependent) Explore new theories for artificial neural network design to both to improve recognition performance, and to develop new modeling frameworks.


  • PhD in Biological Sciences, Neuroscience, Statistics, Computer Science or Engineering but must have a strong background in computational work. Additional skills preferred include experience with computer vision, deep learning, probabilistic modeling, GPU computing and/or data science more broadly.

Application Instructions:

  • Applicants should submit a current resume, names of 2-3 references, and an indication of the project area they are interested in exploring. Optionally, applicants may submit code samples or a GitHub repository representative of experience with computational work.


Application Details

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