<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">About Truveta</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<p><span data-contrast="none">Truveta provides unprecedented real-world data and real-time intelligence, powered by a dataset built with and owned by US health systems united in a mission of Saving Lives with Data. Together, we power breakthrough medical discoveries, accelerate regulatory-grade evidence, and improve patient care. Today, Truveta enables research on more than 130 million de-identified patients across the US. </span><span data-ccp-props="{"134233117":true,"134233118":true,"201341983":0,"335551550":1,"335551620":1,"335559685":0,"335559737":0,"335559740":240}"> </span></p>
<p><span data-contrast="auto">Achieving Truveta’s ambitious mission requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our </span><a href="https://www.truveta.com/careers/"><span data-contrast="none"><span data-ccp-charstyle="Hyperlink">company values</span></span></a><span data-contrast="auto">. </span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559738":0,"335559739":160,"335559740":278}"> </span></p>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">The Role</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<p><span data-contrast="auto">We are seeking a highly motivated </span><strong><span data-contrast="auto">Postdoctoral Researcher</span></strong><span data-contrast="auto"> to explore and develop novel applications of cutting-edge AI/ML technologies on large-scale real-world clinical data.</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559738":210,"335559739":210,"335559740":278}"> </span></p>
<p><span data-contrast="auto">This role is designed for recent PhD graduates who are passionate about pushing the boundaries of machine learning in healthcare. You will work at the intersection of </span><strong><span data-contrast="auto">machine learning, clinical data, and biomedical science</span></strong><span data-contrast="auto">, identifying new opportunities where modern AI can unlock insights that were previously out of reach.</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559738":210,"335559739":210,"335559740":278}"> </span></p>
<p><span data-contrast="auto">A key expectation is not just execution—but </span><strong><span data-contrast="auto">imagination</span></strong><span data-contrast="auto">: the ability to envision and prototype entirely new ways to use rich patient data to solve meaningful healthcare problems.</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559738":210,"335559739":210,"335559740":278}"> </span></p>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">What </span><span data-ccp-parastyle="heading 3">You’ll</span><span data-ccp-parastyle="heading 3"> Do</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":1,"335551620":1,"335559685":0,"335559737":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<ul>
<li data-leveltext="" data-font="Symbol" data-listid="11" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">Innovate: Identify and propose novel, high-impact applications of AI/ML using large-scale EHR data</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":1,"335551620":1,"335559737":0,"335559738":210,"335559739":210,"335559740":278}"> </span></li>
</ul>
<ul>
<li data-leveltext="" data-font="Symbol" data-listid="11" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">Research & Prototype: Design, develop, and evaluate state-of-the-art models (e.g., foundation models, multimodal learning, causal ML, generative AI)</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":1,"335551620":1,"335559737":0,"335559738":210,"335559739":210,"335559740":278}"> </span></li>
</ul>
<ul>
<li data-leveltext="" data-font="Symbol" data-listid="11" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">Work Across Modalities: Integrate structured and unstructured EHR data with emerging data types such as genomics, imaging, and clinical notes</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":1,"335551620":1,"335559737":0,"335559738":210,"335559739":210,"335559740":278}"> </span></li>
</ul>
<ul>
<li data-leveltext="" data-font="Symbol" data-listid="11" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="1"><span data-contrast="auto">Collaborate Cross-Functionally: Partner with clinicians, data scientists, and product teams to translate research ideas into real-world solutions</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":1,"335551620":1,"335559737":0,"335559738":210,"335559739":210,"335559740":278}"> </span></li>
</ul>
<ul>
<li data-leveltext="" data-font="Symbol" data-listid="11" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="5" data-aria-level="1"><span data-contrast="auto">Publish & Share: Contribute to top-tier conferences/journals and represent Truveta in the research community</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":1,"335551620":1,"335559737":0,"335559738":210,"335559739":210,"335559740":278}"> </span></li>
</ul>
<ul>
<li data-leveltext="" data-font="Symbol" data-listid="11" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"","469777815":"hybridMultilevel"}" data-aria-posinset="6" data-aria-level="1"><span data-contrast="auto">Explore the Unknown: Proactively identify problems that have not yet been addressed and define new research directions</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":1,"335551620":1,"335559737":0,"335559738":210,"335559739":210,"335559740":278}"> </span></li>
</ul>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">What </span><span data-ccp-parastyle="heading 3">We’re</span><span data-ccp-parastyle="heading 3"> Looking For</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">Minimum Qualifications</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">PhD in Computer Science, Machine Learning, Biomedical Informatics, or a related field</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">Strong background in machine learning, deep learning, or statistical modeling</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">Experience applying ML to healthcare, biomedical, or clinical datasets</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="6" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="1"><span data-contrast="auto">Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow)</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">Preferred Qualifications</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">Experience with healthcare data (EHRs, claims, clinical notes) or biomedical data (genomics, imaging)</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">Familiarity with cutting-edge areas such as: </span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="o" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":1,"335559684":-2,"335559685":1440,"335559991":360,"469769226":"Symbol","469769242":[9675],"469777803":"left","469777804":"o","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="2"><span data-contrast="auto">Foundation models / LLMs in healthcare</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":1440,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="o" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":1,"335559684":-2,"335559685":1440,"335559991":360,"469769226":"Symbol","469769242":[9675],"469777803":"left","469777804":"o","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="2"><span data-contrast="auto">Multimodal learning</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":1440,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="o" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":1,"335559684":-2,"335559685":1440,"335559991":360,"469769226":"Symbol","469769242":[9675],"469777803":"left","469777804":"o","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="2"><span data-contrast="auto">Causal inference</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":1440,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="o" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":1,"335559684":-2,"335559685":1440,"335559991":360,"469769226":"Symbol","469769242":[9675],"469777803":"left","469777804":"o","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="2"><span data-contrast="auto">Representation learning on longitudinal data</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":1440,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">Track record of publications in top-tier ML or healthcare venues (e.g., NeurIPS, ICML, ICLR, MLHC, AMIA)</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="7" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="1"><span data-contrast="auto">Ability to work across disciplines and communicate with both technical and clinical stakeholders</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<p><span data-contrast="auto"> </span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559738":0,"335559739":160,"335559740":278}"> </span></p>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">Who You Are</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="8" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><strong><span data-contrast="auto">Curious and imaginative:</span></strong><span data-contrast="auto"> You naturally think beyond existing solutions and ask “what hasn’t been done yet?”</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="8" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><strong><span data-contrast="auto">Impact-driven:</span></strong><span data-contrast="auto"> You care about applying research to real-world healthcare problems</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="8" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><strong><span data-contrast="auto">Comfortable with ambiguity:</span></strong><span data-contrast="auto"> You thrive in open-ended environments where defining the problem is part of the job</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="8" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="1"><strong><span data-contrast="auto">Collaborative:</span></strong><span data-contrast="auto"> You enjoy working across domains and learning from experts in different fields</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<p> </p>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">Why This Role is Unique</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="9" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">Access to one of the largest and richest longitudinal EHR datasets in the US</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="9" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">Opportunity to work on </span><strong><span data-contrast="auto">previously infeasible problems</span></strong><span data-contrast="auto"> at the intersection of AI and medicine</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="9" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">A balance of </span><strong><span data-contrast="auto">academic-style research freedom</span></strong><span data-contrast="auto"> and </span><strong><span data-contrast="auto">real-world impact</span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="9" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="1"><span data-contrast="auto">Collaboration with leading healthcare systems and industry partners</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<p> </p>
<p><strong><span data-contrast="none"><span data-ccp-parastyle="heading 3">Example Problem Areas (Illustrative)</span></span></strong><span data-ccp-props="{"134233117":false,"134233118":false,"134245418":true,"134245529":true,"201341983":0,"335551550":0,"335551620":0,"335559738":246,"335559739":246,"335559740":278}"> </span></p>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="1" data-aria-level="1"><span data-contrast="auto">Learning patient trajectories using foundation models for clinical decision support</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="2" data-aria-level="1"><span data-contrast="auto">Discovering novel phenotypes or disease subtypes from multimodal data</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="3" data-aria-level="1"><span data-contrast="auto">Predicting treatment effectiveness using causal ML on real-world data</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="4" data-aria-level="1"><span data-contrast="auto">Generating synthetic cohorts for rare disease research</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>
<ul>
<li data-leveltext="·" data-font="Symbol" data-listid="10" data-list-defn-props="{"335552541":1,"335559683":0,"335559684":-2,"335559685":720,"335559991":360,"469769226":"Symbol","469769242":[8226],"469777803":"left","469777804":"·","469777815":"hybridMultilevel"}" data-aria-posinset="5" data-aria-level="1"><span data-contrast="auto">Integrating genomics + EHR for precision medicine applications</span><span data-ccp-props="{"134233117":false,"134233118":false,"201341983":0,"335551550":0,"335551620":0,"335559685":720,"335559737":0,"335559738":0,"335559739":0,"335559740":278,"335559991":360}"> </span></li>
</ul>