Computational research positions

We’re excited about a new initiative applying recommender systems to genomics, and are looking to hire for multiple positions. Due to the pandemic, we are currently working mostly remote, and have flexibility to consider applicants from across the USA and beyond. Positions available immediately, until filled.

Background and directions

The traditional way of analyzing genomics data is severely limited due to a chronic lack of broader context: most experiments and analyses are performed in isolation, and high specialization levels of individual scientists preclude a birds-eye view across datasets. At the same time, consumer-facing web businesses have long understood the value of learning from patterns collected across large corpora of data, to better serve customers, maximize investment returns and prioritize future directions. This gap between current practice in genomics and ultimate potential forms the overarching motivation for our work: we aim to enable the full potential of large-scale genomic datasets through the use of machine-assisted approaches. These ideas represent an essential and inevitable transition towards “augmented genomics”, a new field in which the work of genome scientists is supplemented by data-driven machine intelligence.

Available Positions

We’re currently hiring computational postdoctoral researchers as well as otherwise experienced computational scientists.

Domain expertise in computational biology (in particular chromatin genomics) and recommender systems is preferred but not strictly required. What is important, is your enthusiasm for the subject matter, and an aptitude for large scale data exploration and analysis.

An ideal candidate should possess at least several of the following:

  • PhD in (computational) genomics or a related field (for the postdoc position)
  • Publications in peer-reviewed journals and conferences (for the postdoc position)
  • Experience managing projects and mentoring people
  • Fluency in Python and/or R
  • Good at (graphically) summarizing large amounts of data
  • Demonstrated experience with applying machine learning models to genomics data
  • Working knowledge of information retrieval processes or recommender systems
  • Academic background and expertise in (a field related to) chromatin genomics
  • A curious mind, with great attention to detail
  • Good communication skills, both spoken and written

If you are unsure about how you could contribute or fit in, please do not self-select yourself out, but let’s talk. People from traditionally underrepresented groups are particularly encouraged to apply: we want to hear from you. If you have relevant experience and want to apply this to genomics, this is a great opportunity to make a big impact!

Research environment

Dr. Meuleman’s research interests span genome organization, regulatory genomics, computational epigenomics and large-scale data integration & visualization. We operate as a small group of 5-6 people, and aim for a research environment driven by curiosity, collaboration, veracity, and inclusion, so that we can do our best work together. This environment includes a strong commitment to training and teaching of skills required, and an expectation of working with enthusiastic self-motivating people.

Working at the Altius Institute

The Altius Institute for Biomedical Sciences is a non-profit research institute with ~80 people, located on Seattle’s waterfront right next to Pike Place Market. Beyond great food, coffee & culture, Seattle offers plenty of skiing, hiking & camping opportunities less than an hour away. Altius offers amazing employment benefits, including matched retirement fund contributions, generous time off (incl. paid holidays and parental leave), great medical/dental/vision plans, commuter benefits & much more.

Other available positions

In addition to the positions listed above, we further have openings in the areas of:

  1. regulatory genome organization and annotation,
  2. large-scale genomic data visualization and
  3. synthetic sequence generation using machine learning models.

How to apply

To apply, please submit the following material to

  • curriculum vitae
  • a cover letter outlining previous experience, current interests and career goals
  • contact information for three references

Inquiries about these and other positions are welcome and encouraged. Please contact Dr. Wouter Meuleman by email ( or via Twitter DM (@nameluem).