Skip to content

Open nowPosted 22 days ago

PhD student (Wearable Mobility Sensing )

MyCareersFuture94,028 open roles

Pay
SGD 4,300 – SGD 6,300 a month
Where
West, Singapore
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowPhD student (Wearable Mobility Sensing )MyCareersFuture · West, Singapore
  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on MyCareersFuture's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

7.7% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 1.6%1 day
  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 22 days ago

The posting

About TUMCREATE

TUMCREATE is a multidisciplinary research platform of the Technical University of Munich (TUM) at the Singapore Campus for Research Excellence and Technological Enterprise (CREATE). We are partnering with universities, public agencies, and industry to advance future technologies.

The HEARTwise project is a public-private research initiative funded by Singapore's National Research Foundation, bringing together clinical cardiologists (CADENCE / NUHS, NHCS),engineers from TUM and TUMCREATE, and MedTech partners. The project develops a multimodal platform for non-invasive, early decompensation detection in ambulant HF patients - combining wearable mobility sensing, acoustic environment recognition, and integration with additional digital biomarkersources.

As a member of the HEARTwise team, you will collaborate within an interdisciplinary consortium comprising leading experts in cardiology, telemedicine, biomedical engineering, acoustics, data privacy, and industry.

Please visit www.tum-create.edu.sg for more information about TUMCREATE.

Job Title/Position

Research Associate / PhD candidate (Wearable Mobility Sensing and Digital Biomarkers for Heart Failure Monitoring)

Background & Scientific Context

Heart failure (HF) affects 2.5% of Singapore's population and is the leading cardiac cause of hospital admission -presenting a decade earlier and more aggressively than in Europe or North America. The 30% rehospitalization rate within 90 days of discharge is both a major clinical burden and a window of opportunity for early, data-driven intervention.

This is a fixed-term contract until March 2029 when applicable.

Supervision & Academic Environment

The position is jointly supervised by principal investigators at TUM Munich and TUMCREATE Singapore, with close integration into the CADENCE clinical network. The candidate will work within a growing team of researchers across engineering and clinical disciplines in Singapore, with strong links to the Munich ecosystem. The position combines the rigor of TUM's doctoral program with direct access to clinical partners and the unique research infrastructure of TUMCREATE.

The Research Position

This PhD is embedded in the HEARTwise engineering team at TUMCREATE Singapore and is centered on the actibelt®wearable technology platform - a body-worn 3D accelerometer system with a mature clinical track record, an established algorithm library, and over 64 years of recorded patient data. The core scientific contribution expected is the development, validation, and clinical deployment of actibelt-based mobility analysis in HF patients.

The candidate will engage with open methodological questions - including how to extract richer clinical information from inertial data, how to improve reference data acquisition for algorithm development, and what mobility-based signatures may carry predictive value for HF decompensation - as well as with the translational challenge of deploying these methods in a real clinical setting.

Central research questions include:

  • Which mobility parameters derivable from belt-worn inertial sensing are most informative for detecting early functional deterioration in ambulant HF patients?
  • What methodological advances in reference data acquisition, sensor placement, or algorithm generalization can improve the quality and scalability of wearable-based gait analysis?
  • How can a prototype clinical decision support tool effectively integrate actibelt-derived mobility markers with additional digital inputs to inform clinical management?

Your Responsibilities

Core project deliverables:

  • Validate and adapt actibelt® technology for HF patient monitoring in Singapore, extracting and evaluating mobility parameters (real-world walking speed, stair-climbing ability, gait quality indices)
  • Contribute to the design and execution of a clinical pilot study (35 HF patients + reference cohort) at NHCS/NUHCS
  • Contribute to a prototype clinical decision support system integrating actibelt-derived parameters with additional digital inputs (e.g., digital stethoscope, digital scale)
  • Publish findings in peer-reviewed journals and present at international conferences
  • Contribute to the CACOM lecture series(Clinical Applications of Computational Medicine, TUM)

Research and methodological development:

  • Design and pursue original research questions within the project's scientific scope
  • Develop and evaluate novel algorithmic approaches for inertial signal processing, activity classification, or clinical endpoint extraction
  • Contribute to the broader actibelt algorithm development pipeline, including work on reference data collection methodology and algorithm validation frameworks
  • Engage across the HEARTwise consortium and bring your own scientific perspective to collaborative discussions

Required Qualifications:

  • Master's degree in Biomedical Engineering, Electrical Engineering, Computer Science, Data Science, Health Informatics, or a closely related field
  • Strong interest in wearable technology,digital health, and translational research
  • Solid programming skills (Python, R,MATLAB, Julia, or similar)
  • Experience in signal processing,time-series analysis, or machine learning

Highly valued:

  • Background in algorithm development for inertial, acoustic, or physiological sensor data
  • Experience with clinical datasets or familiarity with clinical research environments
  • Genuine curiosity about open methodological questions and the ability to pursue them independently
  • Ability to thrive in interdisciplinary teams spanning engineering, medicine, and data science
  • Excellent communication skills in English

What we offer

  • Fully funded PhD position within a well-resourced international collaboration
  • Joint supervision by leading experts at TUM Munich and TUMCREATE Singapore
  • Active engagement with a growing interdisciplinary research team on-site in Singapore, with regular exchanges with Munich
  • Access to the TUM and CADENCE/CADENCE-Singapore networks (NUHS, NHCS, NTU, and beyond)
  • Unique real-world clinical datasets and deep access to the actibelt® technology platform and data ecosystem
  • Genuine freedom to shape research questions within a meaningful applied and clinical context
  • Support for conference participation,visits to Munich, and scientific publication

Applications

Please submit the following essential documents to [email protected]:

  • CV
  • Motivation letter (describing your research interests and why this position appeals to you)
  • Academic transcripts
  • Contact details of two referees

Only shortlisted candidates will be contacted.

We look forward to your application!

From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against MyCareersFuture's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.
  3. We apply on MyCareersFuture's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.
  4. Every reply, sorted

    MyCareersFuture's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.
  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

By hand5–10
With CV Rocket100
applications a day

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.