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PhD Position in data-driven characterisation of paediatric sepsis in Zürich

Studierende finden an der ETH Zürich ein Umfeld, das eigenständiges Denken fördert, Forschende ein Klima, das zu Spitzenleistungen inspiriert.

Jobbeschreibung

100%, Zurich, fixed-term

The Biomedical Data Science Lab investigates data-driven solutions for healthcare applications with a focus on neurological conditions such as spinal cord injury, lower back pain, neuro-degenerative disorders and neurological tumors. At the core of our research is the collaboration across disciplines spanning expertise in medicine, biology, computer and data science. The ICU of the University Children’s Hospital Zurich conducts innovative research projects in an interdisciplinary team to improve patient care. Our practice-oriented research focus ranges from cardiovascular and respiratory support to asphyxia and neuroprotection, with a particular interest in sepsis in children. We are seeking a motivated PhD to join this growing team and contribute to interdisciplinary research partnerships.

You will work at the interface of the ETH Zurich and the University Children’s Hospital Zurich to use machine learning for sepsis early detection. ETH Zurich is one of the world’s leading universities specializing in science and technology. The University Children’s Hospital is the largest university children's hospital in Switzerland with about 2,500 employees, and is one of the leading centers for pediatric and youth medicine in Europe. Zurich is a major European research hub that also offers an exceptionally high quality of life.

Project background

Sepsis is a leading cause of mortality in children worldwide. A major limitation in pediatric sepsis management is the delay in obtaining accurate diagnosis because children with sepsis initially often have symptoms akin to common and mild viral illnesses. Rapid and reliable diagnosis of sepsis is a major unmet clinical need, which will be addressed in the proposed project. The goal of this large and innovative project is to improve the diagnosis of pediatric sepsis by assessing the host response using so-called “omics”. Specifically, we will measure the host response at protein (proteomics) and metabolic (metabolomics) level, in addition to the gene expression (transcriptomics). Thereby, we hope to identify novel markers which can improve the diagnosis and management of sepsis in children. Using machine learning on this unique dataset, we aim to characterize the individual response to sepsis. Thereby we hope to identify new avenues for better, more personalized sepsis management.

This project is funded by the Personalized Health and Related Technologies (PHRT) strategic focus area of the ETH.

 

Job description

As a PhD student, you will be an integral part of our research team and actively contribute to the development and implementation of data-driven approaches for early sepsis detection. You will have access to a vast array of anonymized patient data, state-of-the-art computing resources, and a collaborative work environment. Under the guidance of experienced researchers, you will have the opportunity to shape the direction of the project and conduct cutting-edge research in the field of healthcare analytics.

Responsibilities:

  • Conduct a comprehensive review of existing literature on sepsis detection, data analytics, and machine learning techniques
  • Collaborate with clinicians and researchers to identify relevant data sources and variables for analysis
  • Develop and implement machine learning models and algorithms to detect early signs of sepsis
  • Analyze and interpret complex data sets to identify novel patterns and biomarkers
  • Validate and evaluate the performance of the developed models using real-world data
  • Document research findings in academic publications and present at them conferences
  • Contribute to the collaborative and interdisciplinary research environment
Your profile

Qualifications:

  • A master's degree in computer science, data science, computational biology, biomedical engineering, or a related field
  • Strong programming skills, preferably in Python
  • Experience working with large datasets and data processing tools
  • Solid understanding of data analysis and machine learning techniques
  • Excellent written and oral communication skills in English
  • Ability to work independently and collaboratively in a team environment
  • Highly organized with excellent communication and interpersonal skills

Preferred Qualifications:

  • Experience with machine learning algorithms and software (e.g., TensorFlow, PyTorch)
  • Familiarity with biomedical data and research
  • Experience with database management systems (e.g., SQL)

 

Your workplace
Your workplace



We offer
  • Opportunities to engage in cutting-edge research with the potential for high impact for pediatric patients with sepsis
  • Opportunities for professional development
  • Opportunities to engage with different communities bridging data science and medicine research leading to high-impact publications
  • You will be part of a highly motivated, friendly and collaborative team
  • You will be able to attend relevant (inter-) national conferences to increase your visibility and present the project outcomes
  • You will be involved in the supervision of master students and teaching activities of the lab
We value diversity
In line with , ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our to find out how we ensure a fair and open environment that allows everyone to grow and flourish.
Curious? So are we.

We look forward to receiving your online application with the following documents:

  • A letter of motivation (1-page max)
  • CV 
  • MSc and BSc diploma 

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Questions regarding the position should be directed to Prof. Catherine Jutzeler and Dr. Sarah Brueningk, by email at catherine.jutzeler@hest.ethz.ch and sarah.brueningk@hest.ethz.ch (no applications).

We evaluate applications on a rolling basis. 

About ETH Zürich
ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Veröffentlicht am

29-02-2024

Extra Informationen

Status
Inaktiv
Standort
Zürich
Jobart
Werkstudentenstelle
Tätigkeitsbereich
Technik / Elektronik
Führerschein erforderlich?
Nein
Auto erforderlich?
Nein
Motivationsschreiben erforderlich?
Nein

Zürich | Technik Stellenangebote | Werkstudentenstelle