Job opportunity
Dr. Daniel A. Richards and Professor Andrew J. deMello, at the Institute for Chemical and Bioengineering at ETH Zürich, are searching for two postdoctoral researchers to develop a diagnostic device for multidrug resistant Mycobacterium tuberculosis (MDR-MTB). The aim is to create a simple, portable, and affordable device for diagnosing MDR-MTB at the point-of-care. This work is funded as part of a SNSF BRIDGE Discovery grant, and you will collaborate within a multi-institutional consortium that includes the Swiss Centre for Microelectronics (CSEM), the Swiss Tropical Public Health Institute (Swiss TPH), and the National Centre for Tuberculosis and Lung Disease (NCTLD) in Tbilisi, Georgia. The first position requires a candidate with a background in electrochemical biosensing, especially those experienced in combining molecular biology with electrochemistry. The second position seeks a candidate with expertise in electrical engineering and device development. These positions are fixed-term for 24 months initially, with the possibility of extension.
Tuberculosis (TB) kills an estimated 1.25 million people each year, making it the deadliest infectious disease globally. TB disproportionately impacts low- and middle-income countries (LMICs); 98% of global TB cases occur within LMICs, leading to devastating effects. The proliferation of this disease has resulted in widespread misuse of antibiotics, leading to significant drug resistance. In the worst affected regions, drug resistance among recurring TB infections has surpassed 50%.
Most TB deaths are preventable if diagnosed early. However, nearly a quarter of all TB cases go undiagnosed. Additionally, the increasing drug resistance in TB can be partly attributed to a lack of effective methods for identifying resistance markers, which leads to poor antibiotic stewardship. Contemporary diagnostic technologies have proven inadequate for diagnosing TB and associated drug resistances, especially at the point-of-care (PoC). Few technologies can quickly and accurately diagnose TB while simultaneously determining resistances, and those that do are often large and costly, precluding their use in LMICs. They also heavily depend on sputum samples, which can be challenging to obtain in low-resource settings.
This project aims to develop an affordable, portable, and rapid diagnostic platform that can multiplex 14 targets for TB and associated markers of drug resistance from a single sample. This technology will be paper-based and will utilize electrochemical signaling to facilitate miniaturization and provide quantitative disease readouts. The paper-based tests will employ a recently patented technology from ETH Zurich, specifically the laser-induced graphenization of cellulose. This manufacturing process is cost-effective, scalable, and rapid, making it ideal for constructing PoC devices. The technology will be integrated with novel CRISPR-Cas-based biosensing assays tailored for detecting single-nucleotide polymorphisms (SNPs) linked to drug resistance. To support deployment at the PoC, we will harness the facilities and expertise of CSEM to create a highly affordable cartridge and reader system. The research team will be supported by the Swiss Tropical and Public Health Institute and the National Center for Tuberculosis and Lung Disease in Georgia, who will validate the technology using patient samples and conduct a small pilot study.
This device will address a critical gap in the current treatment pathway for TB and provide care to millions of underserved patients, particularly in LMICs. By enabling rapid diagnosis of TB, this technology will facilitate more accurate and timely medical interventions, ultimately improving patient outcomes and reducing burdens on healthcare systems. Furthermore, by targeting common drug resistance markers, this technology will enhance antimicrobial stewardship and contribute significantly to the fight against antimicrobial resistance (AMR).
We invite applications from computer scientists and/or imaging experts eager to gain expertise in bioengineering, IVDs, and global health, as well as researchers with experience in IVDs looking to transition towards mHealth and computer science. Proficiency in coding is essential. Previous experience in writing code for automating high-throughput image capture and analysis, as well as app development, is advantageous.
Candidates should possess a PhD in a relevant science or engineering discipline. However, we will evaluate candidates based on their overall experience, expertise, and ambitions, rather than solely on specific research disciplines. Successful candidates will join an international research team and are expected to display high motivation and passion for science, engineering, and global health.
ETH Zurich is a leading institution known for its excellence in science and technology research. We pride ourselves on fostering an international, collaborative environment that values diversity and sustainability.
Apply online using the form below. Only applications matching the job profile will be considered.
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