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    <h2>The Ronquist Lab</h2>
    <h3>Computational biology and insect diversity</h3>
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    <p>The Ronquist lab is an interactive and interdisciplinary environment, where we focus on innovative research at the interface between statistics, computer science, evolutionary biology, and insect diversity. We have co-authored some of the leading software packages for Bayesian analysis of phylogenetic problems, and continue to develop new computational approaches, models and inference strategies. The current focus is on universal probabilistic programming. In our empirical research on insect diversity and evolution, we also strive to explore new directions. Recent examples include deep learning for automated image-based identification, improved methods for finding genes linked to life-history changes, more efficient molecular techniques for rapid species discovery, and genetic analyses that scale so that we can analyze the composition and function of entire insect faunas and their associated microbiomes.</p>

    <h2>News</h2>

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    <p><strong>Postdoc in probabilistic programming</strong><br />
      2020-11-24
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      We are looking for a postdoc interested in developing new modeling and inference tools based on universal probabilistic programming, an approach that has attracted considerable attention across scientific disciplines in recent years. Specifically, we will be developing a domain-specific language to describe phylogenetics problems, and design new inference strategies for such model descriptions. The goal is to successfully tackle some of the most challenging research problems in statistical phylogenetics and phylogenomics. For some early success stories, see our recent <a href="https://doi.org/10.1101/2020.06.16.154443">paper on bioRxiv</a>. The postdoc will be encouraged to develop new projects, apply for third-party funding, supervise students and lecture at courses. Read more and apply <a href="https://www.nrm.se/en/ommuseet/jobbahososs/ledigatjanster.9005019.html">here</a>. <b>Application deadline December 18.</b></p>

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    <p><strong>Unique insect data published</strong><br />
      2020-11-24
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      The Swedish Malaise Trap Project (SMTP) is q unique contrywide inventory of a national insect fauna. The field campaign was completed in 2003-2006, and sampled the insect fauna at 73 different selected sites across the ccountry using Malaise traps. The entire catch is estimated to contain some 20 million insect specimens. This unique project is now described in <a href="https://doi.org/10.3897/BDJ.8.e47255">a recent paper of ours</a> in Biodiversity Data Journal. More than 100 taxonomic experts have participated in the identification of the material so far. Around 170,000 specimens, about 1 &percnt; of the total material, have been determined to species. What is unique about these data is that they are focused to a large extent on poorly known groups in the insect orders Hymenoptera and Diptera, groups that are rarely processed in similar inventories for lack of taxonomic expertise. The available SMTP data have recently been published to GBIF as 79 sample-based datasets, as described in <a href="https://bdj.pensoft.net/article/56286/list/9/">another recent paper</a> of ours, also in Biodiversity Data Journal.

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      Thanks in large part to the SMTP inventory, the known Swedish insect fauna has increased with 2,000 species in the last decade, to 28,000 species. Our <a href="https://doi.org/10.1371/journal.pone.0228561">recent analysis</a> based on the inventory data suggests that as many as 5,000 additional insect species may still remain to be discovered in Sweden, many of them likely new to science. Most of the remaining species belong to Hymenoptera and Diptera, and many of them are decomposers or parasitoids.</p>

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    <p><strong>2019 Publisher's Award for Excellence in Systematic Research Awarded to Miroslav</strong><br />
      2020-11-16
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      We are proud to announce that Miroslav Valan, one of the PhD students in the lab, was one of two winners of the <a href="https://www.systbio.org/publishers-award.html">2019 Publisher’s Award for Excellence in Systematic Research</a>. The award is presented to the two best papers based on student research published in Systematic Biology during the previous year. The lead author must have been a student at the time the research was conducted. Miroslav won the prize for his <a href="https://academic.oup.com/sysbio/article/68/6/876/5368535">paper developing methods</a> for automated image-based identification of insects based on convolutional neural networks and feature transfer.</p>
    
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    <p><strong>Hakuna Ma-Data Microsoft Sponsored Competion Won by Miroslav</strong><br />
      2020-11-16
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      Miroslav Valan, one of the PhD students in the Ronquist lab, recently won the <a href="https://www.drivendata.org/competitions/59/camera-trap-serengeti/">Hakuna Ma-Data</a> competition sponsored by Microsoft. The task was to automatically identify species of wildlife in camera trap images from the Serengeti National Park. His contribution placed first among contributions from over 800 teams, earning him a $20,000 contribution to his research. <a href="https://arxiv.org/abs/2008.07828">Miroslav’s solution</a> was presented at the prestigious computer-vision conference CVPR 2020.</p>

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