UCLA PhD & Postdoc Openings in CS & CompMedicine47 Views

Introduction: Why These UCLA Opportunities Matter

UCLA PhD and postdoc positions in computer science and computational medicine offer a rare chance to work at the frontier of machine learning, health, and scientific discovery. This article explains how these positions are structured, why the CS and CompMed programs are attractive pathways, what kind of background is expected, and how to prepare a strong application that is aligned with the lab’s research direction.

Prof. Yuzhe Yang announced that his new lab at UCLA is recruiting PhD students and postdoctoral researchers through the Computer Science (CS) and Computational Medicine (CompMed) PhD programs, with a focus on foundation models and generative AI for health, medicine, and science.

Why Combine Computer Science and Computational Medicine at UCLA?

UCLA brings together a highly ranked Computer Science department and a distinctive Department of Computational Medicine that links mathematics, statistics, and biology. Consequently, students and postdocs can develop new algorithms while working directly with clinical data and collaborators at UCLA Health.

Prof. Yang’s research centers on robust machine learning and foundation models for multimodal biomedical data, including medical images, electronic health records, and physiological signals. Therefore, researchers joining his group can expect a combination of theoretical work, large-scale empirical studies, and close interaction with clinicians and scientists.

Foundation models

and generative AI are used in this setting to represent complex biomedical information, to reason about uncertainty, and to study fairness and robustness in health AI systems. For applicants who already enjoy deep learning, statistics, and optimization, this environment offers a natural way to translate core technical skills into high-impact medical applications.

Program Paths: UCLA CS PhD and CompMed PhD

There are two main PhD routes into the lab: Computer Science and Computational Medicine.

UCLA Computer Science PhD Program

The UCLA Computer Science PhD program admits students for the Fall term only. According to departmental guidance, applicants submit the UCLA graduate application by around 15 December each year for admission in the following academic year.

Crucially, all admitted CS PhD students are provided financial support, typically through a combination of fellowships, teaching assistantships, and research assistantships funded by faculty grants. This structure allows students to concentrate on research from the very beginning.

Once admitted, students can indicate their interest in working with specific faculty, including Prof. Yang, and then explore research fit through meetings, lab rotations (where available), or direct matching depending on department practices.

UCLA Computational Medicine PhD Program

The Computational Medicine PhD program, rooted in the Biomathematics tradition, trains researchers who combine quantitative depth with biomedical breadth. The

program’s admissions page lists a typical deadline of 1 December, with early offers that include funding extended in the following months.

This track is particularly suitable for applicants with strong mathematics, statistics, physics, or engineering backgrounds who wish to make biomedical data their primary research domain while still working at the cutting edge of machine learning and AI.

Who Should Apply to These UCLA Positions?

These opportunities target highly motivated researchers at two stages: new PhD students and postdoctoral fellows.

Profiles for PhD Applicants

Competitive PhD applicants usually have:

• • A strong bachelor’s or master’s degree in computer science, electrical engineering, mathematics, statistics, biomedical engineering, or a closely related field.
  • Prior research experience in machine learning, AI, data science, or computational biology, ideally with a thesis, technical report, or publication.
  • Clear motivation to work on foundation models, generative AI, or responsible AI methods for health and medicine.

In addition, familiarity with modern deep learning frameworks, large-scale data processing, and interdisciplinary collaboration will significantly strengthen the application.

Profiles for Postdoctoral Candidates

Postdoctoral candidates are expected to have completed a PhD in a closely related area and to bring a solid publication record in venues such as NeurIPS, ICML, ICLR, or leading clinical and biomedical journals. Moreover, they should be able to drive research directions independently, mentor junior students, and articulate

a medium-term agenda for generative AI in health and science.

Funding, Supervision, and Research Environment

Financially, admitted CS PhD students receive guaranteed support. Similarly, Computational Medicine aims to admit fully funded candidates. In addition, UCLA Graduate Division offers many competitive fellowships and travel awards. These can supplement the standard package and fund conference trips or specialized training.

Scientifically, Prof. Yang holds a joint appointment across the Henry Samueli School of Engineering, the David Geffen School of Medicine, and UCLA Health. Consequently, lab members can collaborate with clinicians, biostatisticians, and experimental scientists. This provides access to rich multimodal datasets and real clinical questions, rather than purely synthetic benchmarks.

How to Apply: Practical Steps

Although the lab is actively recruiting, applications for PhD positions must go through the official UCLA degree programs.

Applying to the UCLA CS PhD Program

First, review the CS graduate program pages to confirm eligibility, required coursework, and research areas. Next, prepare the core application materials: transcripts, a detailed CV, a statement of purpose, a personal statement, and strong recommendation letters.

In your statement, briefly outline your work in machine learning or data-driven health. Then explain why the UCLA CS PhD program—and Prof. Yang’s lab in particular—fit your long-term goals.

Finally, submit your application through the UCLA Graduate Admissions portal by the posted deadline. This is usually around 15 December; however,

always check the official site because dates can change.

Applying to the CompMed PhD Program

For Computational Medicine, begin by reviewing the PhD overview and curriculum to understand expectations in biomathematics, probability, statistics, and biomedical applications. Then, connect your quantitative training to specific biomedical questions and highlight any work with clinical, imaging, or omics data.

Next, submit your application by the 1 December deadline. The admissions page also notes that early funded offers come later in the cycle. Finally, as with CS, confirm the latest deadlines and requirements on the official website before applying.

Pathways for Postdoctoral Applications

Postdoctoral roles are usually posted on faculty homepages, departmental boards, and professional networks. Therefore, candidates should regularly check Prof. Yang’s homepage for official calls. They should also prepare a focused research statement that shows how their work aligns with the lab’s projects. In addition, they should send a concise email with a CV, key publications, and a brief proposal for future work.

Tips and Common Mistakes

Several clear patterns tend to mark strong applications. Successful candidates highlight one or two deep technical strengths rather than a long list of buzzwords. They also explain how these strengths connect to foundation-model research in health and science. Moreover, their statements of purpose do more than list projects; they reflect on challenges, lessons learned, and realistic next steps.

However, common mistakes appear just as frequently. Some applicants offer vague goals like “using AI to help people” without a concrete plan. Others submit generic letters that could fit any program or overlook the differences between the CS and CompMed tracks. In addition, last-minute submissions often contain avoidable errors, so early and careful preparation is essential.

Conclusion: Should You Apply to UCLA CS or CompMed for These Roles?

UCLA PhD and postdoc roles in computer science and computational medicine suit researchers who want to blend rigorous machine learning with real biomedical impact. Through the CS and CompMed PhD programs, students receive structured training and secure funding. They also gain access to a deeply collaborative research ecosystem. With mentors like Prof. Yuzhe Yang, they can work on foundation models and generative AI that solve meaningful clinical and scientific problems.

If you aim to work at the intersection of AI and medicine, it helps to review the official guidelines early. You should also prepare your materials in advance and target the December deadlines with a clear, well-argued application. For postdocs, these positions can further provide a strong platform for building an independent research career in high-impact health AI, whether in academia or industry.

Key Facts at a Glance

Feature	Details
Program Name	PhD and postdoctoral opportunities in Computer Science and Computational Medicine (Yuzhe Yang Lab, UCLA)
Host Country	United States
Funded By	UCLA Department of Computer Science, Department of Computational Medicine, and external research grants
Duration	PhD typically 4–6 years; postdoc duration varies (often 2–3 years)
Study Mode	Full-time, on-campus
Eligibility	Strong background in CS, math, statistics, engineering, or related fields; research interest in AI for health and medicine
Financial Support	Fully funded PhD positions with tuition and stipend; postdoc salaries funded from grants
Fields of Study	Computer Science, Machine Learning, Artificial Intelligence, Computational Medicine, Biomathematics
Deadline	UCLA CS PhD: usually 15 December; CompMed PhD: usually 1 December (check official sites each year)
Official Website	UCLA CS Graduate Admissions UCLA Computational Medicine PhD

 

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