Ogłoszenie numer: 2651854, z dnia 2019-09-12
Phages4A is a spinoff of the Institute for Information and Communication Technologies (IICT) at the School of Business and Engineering Vaud (HEIG-VD) in Switzerland.
Antibiotic resistance threatens the efficacy of currently-used medical treatments and call for novel approaches to manage multi-drug resistant infections. Phage therapy, the use of viruses (phages) to specifically infect and kill bacteria during their life cycle, is one of the most promising alternatives to antibiotics. It is based on the correct matching between a target pathogenic bacterium and the therapeutic phage. Nevertheless, correctly matching them is a major challenge in clinic use. Currently, there is no systematic method to efficiently predict whether phage-bacterium interactions exist, and these pairs must be empirically tested in laboratory.
Phages4A has developed a unique workflow (will be available as SaaS) that uses as input the genome of a bacteria to predict the phages that can infect and kill it. Based on this information we are able to help create custom bacteriophage cocktails to treat patients with bacterial infections reducing time and cost.
Full Stack Developer
Miejsce pracy: małopolskie
Phages4A is developing a user-friendly, cloud base software tool that for spot test analysis without requiring any investment in new equipment or changes in the laboratory. It allows standardization and management of spot test experiments.
Spot test are widely applied to determine the antimicrobial susceptibility of microorganisms. The classification of the type of lysis is frequently performed manually by specialists based on his experience. This is a time-consuming and error-prone task that might be simplified using automated or semi-automated inhibition zone readers. However, most readers are usually expensive instruments with embedded software that require significant changes in laboratory design and workflow. In addition, the information from the experiments performed by the microbiologist is not always recorder in the same way. In some cases, notes about the experiments are taken on paper, some plate pictures are erased or excel sheets with different formats are used. It leads to a no digital transability information of the experiments and poor standardization.
Based on the workflow employed by microbiologists to determine the antimicrobial susceptibility of microorganisms, we have designed a software tool that, from images of spot tests, semi- automatizes the process and allow to keep all the information of the experiments (e.g. photos, notes, tables) in a cloud platform, ready to be share or consulted posteriorly. Computer vision techniques and Artificial Intelligence are employed to achieve such an automatization.
We had alredy developed a prof-of-concept version of DeepPetri. It is mainly developed on Phyton. We are looking for a Full stack developer to scale DeepPetri and add new funcionalities.
- Full stack developer
- Highly skilled with Python
- Knowledge in:
- Cloud computing
- machine learning/ Deep learning
- image recognition
- Experience developing "software as a service" products
- Fluent in english.
- Remote job
- At 100%