About the role:

As a Data Scientist at Bioptimus, you will have the opportunity to improve medical research using state-of-the-art machine learning algorithms. You will work within an interdisciplinary team with both machine learning and biomedical expertise to build foundation models of biology that will unlock AI applications and biomedical innovations.

What you will be doing as a Data Scientist:

As an expert Data Scientist in computational biology, you will:

  • Join a team paving the way for the development and application of foundation models in biomedical research.
  • Drive the application of foundation models to relevant biomedical data, including but not limited to genomics, proteomics, single-cell omics and computational histopathology.
  • Design evaluation protocols and leaderboards to guide continual model improvement and alignment with the needs of various stakeholders.
  • Conduct methodological research in key areas to unlock novel applications.This research includes (but is not limited to) writing scientific publications and patents.

Depending on your level of experience, you will have the opportunity to supervise a team and lead ambitious projects.

Who we are looking for:

The successful Data Scientist will have a ‘team-first’ kind of attitude; be independent, curious and detail-attentive; and thrive in a dynamic, fast-paced environment.

And

  • MSc or PhD in computational biology or a related field (bioinformatics, statistics, machine learning, …) or equivalent experience.
  • Demonstrated expertise applying machine learning to computational biology, including scientific publications at high-impact journals (Nature, Science, Cell, Nucleic Acids Research, Genome Biology, …) and/or top conferences in the field (ISMB, RECOMB, NeurIPS, ICLR, ICML, …).
  • Extensive experience working with at least one of genomics, proteomics, single-cell or histology data, encompassing the entire analysis pipeline, from dataset generation and curation based on raw measurements with the appropriate bioinformatics tools, to the application of machine learning models to assess scientific hypotheses and drive novel discoveries.
  • Deep knowledge of best practices in the field, including how to account for noise, common artifacts and batch effects, and mastery of the different evaluation protocols and metrics used in the literature.
  • Excellent written and oral communication skills.

Ways to stand out:

The following are not necessarily required, but would be a plus for the Data Scientist:

  • Good command of coding in python, and willingness to learn about programming best practices and ML engineering for large-scale training and fine-tuning.
  • Familiarity with state-of-the-art machine learning architectures, with an interest in “opening the black box” and learn low-level details of machine learning methodology
  • Hands-on experience implementing custom models with a deep learning framework (PyTorch, Jax, …)

Our company embraces remote work. We follow the guidelines below:

  • You should be able to attend retreats and events in the Paris office (around once a quarter)
  • Remote applicants are expected to have at least a 5-hour overlap with the team in Paris
  • Since we also value in-person work and collaboration, all things being otherwise equal, we will prefer candidates that can connect on a regular basis with the team in Paris

 

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