Career

Sano PhD Student

Project title: Biomedical Semantic Data Integration and Management

Publication date: 9.09.2022

Closing date: 09.10.2022

Level of education: Master's degree

Hours: 40 hours per week

Salary indication: up to 8000 PLN gross monthly

Supervisors:

Sano: dr. Ahmed Abdeen Hamed (Clinical Data Science Research Group Leader)

Project start: October/November 2022

The position is for Sano's Clinical Data Science team. Our group develops a new generation of semantically integrated databases for clinical and biomedical. Our system will build on recent Big Data workflow technologies to integrate using a multitude of very large data sets, including text mining results, mutation databases, internal and external -omics high-throughput sets, ontologies, and clinical data.  

The project sets out to provide an ultimately fine-grained implementation of parsing, extracting, integrating, and querying classes of ontologies which can be processed efficiently and have other desirable computational properties. The overall aim of this approach is to enable ontology engineers to design and customize ontologies that strike an ideal balance between the knowledge provided and efficient processing, in this way developing ontology-mediated querying to its full potential.

The position is especially adequate for Postdocs, PhD students or engineers who want to learn about, apply and further develop workflow technologies for scalable data integration in the exciting field of clinical data science and analytics. You will contribute to the ambition of Sano's Clinical Data Science team to be nationally and internationally recognized for its strengths in clinical data science in general and biomedical data analytics, in particular.

Sano Postdoc

Project title: Biomedical Semantic Data Integration and Management

Publication date: 9.09.2022

Closing date: 09.10.2022

Level of education: PhD

Hours: 40 hours per week

Salary indication: up to 14000 PLN gross monthly

Supervisor:

Sano: Dr. Ahmed Abdeen Hamed (Clinical Data Science collab between PhD student and postdoc)

Project period: October/November 2022

The position is for Sano's Clinical Data Science team. Our group develops a new generation of semantically integrated databases for clinical and biomedical. Our system will build on recent Big Data workflow technologies to integrate using a multitude of very large data sets, including text mining results, mutation databases, internal and external -omics high-throughput sets, ontologies, and clinical data.  

The project sets out to provide an ultimately fine-grained implementation of parsing, extracting, integrating, and querying classes of ontologies which can be processed efficiently and have other desirable computational properties. The overall aim of this approach is to enable ontology engineers to design and customize ontologies that strike an ideal balance between the knowledge provided and efficient processing, in this way developing ontology-mediated querying to its full potential.

The position is especially adequate for Postdocs, PhD students or engineers who want to learn about, apply and further develop workflow technologies for scalable data integration in the exciting field of clinical data science and analytics. You will contribute to the ambition of Sano's Clinical Data Science team to be nationally and internationally recognized for its strengths in clinical data science in general and biomedical data analytics, in particular.

Sano MSc Project

Project title: Accurate sensing and detecting a physical or behavioral health conditions using medical and consumer grade wearables.

Publication date: 06.09.2022

Closing date: 21.09.2022

Level of education: Undergraduate (BSc, BEng)

Hours: approx. 16 working hours per week/40% FTE

Salary indication: stipend for up to 2500 PLN gross monthly

Supervisors:

Dr. Maciej Malawski (Extreme Scale Data and Computing Research Group Leader)

Dr. Tomasz Trzciński (Warsaw University of Technology)

Degree awarding institution: AGH

Project start: September/October 2022

Mobile health (mHealth) applications provide support to patients outside of clinic. They are commonly paired with wearable devices which enable continuous health monitoring and facilitate timely intervention. Nevertheless patients frequently perceive medical wearables as difficult to use and abandon their adoption [1]. Consumer-grade wearables are more widely available and are focused more on the user-friendly design, nevertheless, their physiological signal tracking quality might be varying[2]. Apple watch is a consumer-grade watch that has been also medically approved.

In this project, the student will develop mhealth application for iOS and Apple watch and conduct comparative assessment of usability and signal quality extracted from multiple medical and consumer-grade devices.

Project in collaboration with dr Tomasz Trzcinski, Warsaw University of Technology.

[1] Ferguson, C., Hickman, L. D., Turkmani, S., Breen, P., Gargiulo, G., & Inglis, S. C. (2021). “Wearables only work on patients that wear them”: Barriers and facilitators to the adoption of wearable cardiac monitoring technologies. Cardiovascular digital health journal, 2(2), 137-147.

[2] Saganowski, Stanisław, Przemysław Kazienko, Maciej Dziezyc, Patrycja Jakimów, Joanna Komoszynska, Weronika Michalska, Anna Dutkowiak, A. Polak, Adam Dziadek, and Michal Ujma. "Review of consumer wearables in emotion, stress, meditation, sleep, and activity detection and analysis." arXiv preprint arXiv:2005.00093 (2020).

Study at Sano

Postgraduate study can be a great opportunity to gain advanced training, new skills and in-depth subject knowledge. If you’re thinking about a scientific career, you’re interested in computational medicine and are looking at various options, Sano might be the perfect place for you.

Sano is a new nonprofit research institute dedicated to the advancement of computational medicine, developing sophisticated computer methods for the prevention, diagnosis and treatment of disease, to meet the overarching worldwide need for efficient, effective and streamlined healthcare.

We recognize that it is all about the skills of people involved in the project, to develop Sano into the world-class research centre for advanced computational medicine.

We’re looking for the best people around and invite all students interested in applied research within computational medicine to apply. The MSc programme at Sano is aimed at providing the next generation of healthcare technology innovators with unique skills.

By applying, you will let us know about your interest in education at Sano. We’re looking for students to work at all our Research Groups – Healthcare Informatics, Computer Vision Data Science, Modeling and Simulation, Clinical Data Science, Personal Health Data Science and Extreme-Scale Data and Computing.

We’re waiting for you!

Sano MSc Project

Project title: Cross-device federated learning for medical applications

Publication date: 06.09.2022

Closing date: 21.09.2022

Level of education: Undergraduate (BSc, BEng)

Hours: approx. 16 working hours per week/40% FTE

Salary indication: stipend for up to 2500 PLN gross monthly

Supervisors:

Dr. Maciej Malawski (Extreme Scale Data and Computing Research Group Leader)

Degree awarding institution: AGH

Project start: September/October 2022

The goal of the project is to investigate the applicability of federated learning in a cross-device scenario, in which multiple individual clients use their mobile or personal devices. This is important for patient data analysis of well-being monitoring, in which case the data comes directly from individuals. The plan is to analyze the existing use open source frameworks for federated learning which are compatible with mobile devices (such as Android phones) and build a prototype for evaluation of the performance of the machine learning models, as well as of the distributed environment. The applications scenarios include data from mobile EEG scanners or personal health data from smart watches.

Postgraduate study can be a great opportunity to gain advanced training, new skills and in-depth subject knowledge. If you’re thinking about a scientific career, you’re interested in computational medicine and are looking at various options, Sano might be the perfect place for you.

Sano is a new nonprofit research institute dedicated to the advancement of computational medicine, developing sophisticated computer methods for the prevention, diagnosis and treatment of disease, to meet the overarching worldwide need for efficient, effective and streamlined healthcare.

We recognize that it is all about the skills of people involved in the project, to develop Sano into the world-class research centre for advanced computational medicine.

We’re looking for the best people around and invite all students interested in applied research within computational medicine to apply. The MSc programme at Sano is aimed at providing the next generation of healthcare technology innovators with unique skills.

By applying, you will let us know about your interest in education at Sano. We’re looking for students to work at all our Research Groups – Healthcare Informatics, Computer Vision Data Science, Modeling and Simulation, Clinical Data Science, Personal Health Data Science and Extreme-Scale Data and Computing.

We’re waiting for you!

Sano Postdoc

Project title: Machine learning analysis for brain time series (EEG/fMRI)

Publication date: 31.08.2022

Closing date: 30.09.2022

Level of education: PhD

Hours: 40 hours per week

Salary indication: up to 14000 PLN gross monthly

Supervisor:

Sano: Dr. Alessandro Crimi (Research Group Leader)

Project period: 1 year + extension (e.g. January 2023 - January 2024)

BrainAndMore (BAM) lab focuses cutting edge genetic, molecular and mainly magnetic resonance imaging  technology to understand diseases and support drug development efforts in the neuroscience field.

In this project we want to investigate electrophysiology (EEG and fNIRS) in daily use, as investigating changes in daily use allows to see neurological, psychiatric effects in a broader sense.

Implementation of deep learning/machine learning model for neuroimaging analysis with particular attention to time series.

Sano MSc Project

Project title: Epilepsy seizure detection and dynamical brain connectivity via machine learning

Publication date: 25.07.2022

Closing date: 15.09.2022

Level of education: Undergraduate (BSc, BEng)

Hours: approx. 16 working hours per week/40% FTE

Salary indication: stipend for up to 2500 PLN gross monthly

Sano Supervisor: Dr. Alessandro Crimi (Computer Vision Data Science Research Group Leader)

Dr. Maciej Malawski (Extreme Scale Data and Computing Research Group Leader)

Degree awarding institution: AGH

Project start: September/October 2022

In this project we want to address several questions related to epilepsy. As detection of seizures given a neonatal EEG dataset, with the hope that previous triggers can be identified.

Lastly, analysis of dynamical brain connectivity given by creating multi dimensional graphs will be useful. The focus is mostly on machine learning and complex networks, though knowledge of signal theory (given the EEG data) will be useful. The project will be within a series of larger projects carried out within the lab focused on brain disease and wearables.

Study at Sano

Postgraduate study can be a great opportunity to gain advanced training, new skills and in-depth subject knowledge. If you’re thinking about a scientific career, you’re interested in computational medicine and are looking at various options, Sano might be the perfect place for you.

Sano is a new nonprofit research institute dedicated to the advancement of computational medicine, developing sophisticated computer methods for the prevention, diagnosis and treatment of disease, to meet the overarching worldwide need for efficient, effective and streamlined healthcare.

We recognize that it is all about the skills of people involved in the project, to develop Sano into the world-class research centre for advanced computational medicine.

We’re looking for the best people around and invite all students interested in applied research within computational medicine to apply. The MSc programme at Sano is aimed at providing the next generation of healthcare technology innovators with unique skills.

By applying, you will let us know about your interest in education at Sano. We’re looking for students to work at all our Research Groups – Healthcare Informatics, Computer Vision Data Science, Modeling and Simulation, Clinical Data Science, Personal Health Data Science and Extreme-Scale Data and Computing.

We’re waiting for you!

Sano presents a great opportunity for people who want to make a change in the world by developing life-changing technologies and solutions for healthcare worldwide.

We are looking for an experienced:

Technical Manager

As Technical Manager you will lead and take part in the day-to-day work of the Sano ICT Team   responsible for smooth operations of a wide range of infrastructures managed by Sano both on-premises – including GPU-accelerated servers for AI as well as in the Cloud (public or private). You will also be responsible for creation and update of the ICT-related Policies and Standard Operating Procedures (SOPs) in Sano. 

Additionally, you will be able to assist Sano employees in running software on major High Performance Systems provided for the project by Partners – such as the Prometheus, Ares and Athena Supercomputers (ACC Cyfronet AGH, all systems on TOP500 with Athena on top spot in Poland), clusters at Jülich Supercomputing Center or LUMI Supercomputer (no 3 in the World).

Finally the position on top of management of the team and taking part in the day-to-day operations will allow you to work with interesting and highly advanced technologies such as Private Clouds (esp. OpenStack), Containers (Docker, K8S), data science tools such as Jupyter and more. 

You will also oversee and assist when needed in all other tasks performed by the ICT Team including providing input for the public procurement documentation and taking part in the procurement process. 

Sano PhD Student

Project title: Haptically-enhanced VR/AR for Improved Information Capture and Exchange in Medical/Social Environments

Publication date: 14.07.2022

Closing date: 1.08.2022

Level of education: Master's degree

Hours: 40 hours per week

Salary indication: up to 8000 PLN gross monthly

Supervisors:

Sano: Dr. Przemysław Korzeniowski

Sano: Dr. Arkadiusz Sitek

University of Sheffield: Dr. John Fenner

Project start: September 2022 (but depends on Candidate’s availability)

Degree Awarding Institution: University of Sheffield

This project will investigate the application of state-of-the virtual and augmented reality technologies (VR/AR) in hospital and/or operating room settings. In particular, the project will augment VR/AR with cost-effective accessible haptic technology (sense of touch), which has the capacity to modify everyday clinical practice.

The research aim is to develop a prototype system, which seamlessly integrates with the real clinical environment. As a proof-of-concept, we propose to start with augmenting an angiography suite (CathLab). You will enhance daily-clinical practice of radiographers and interventional cardiologists with haptically-enabled VR/AR surgical planning and/or training tools. 

The effectiveness of this strategy will be evaluated through relevant metrics and questionnaires to judge impact. A successful outcome will promote refinement and urge further acceptance (i.e. translation) within broader medical and technical environments.

We are looking for candidates with an enthusiasm for research, multidisciplinary collaboration and tackling challenging problems through teamwork. We are targeting candidates with an MSc in Computer Science, GameDev or similar,  but we would also consider exceptional STEM students providing that they have appropriate Computer Science skills. Ideal skills would include: programming (C#, C, C++ and/or visual scripting), 3D engines (Unity3D and/or Unreal Engine) and knowledge of git. Nice to have would be 3D modelling skills and/or CAD (Fusion, Solidworks, Blender, Maya and/or 3dsmax) and 3D printing.

You do not need to have a strong background in VR/AR or haptics, but willingness to learn basic concepts and definitions is a requirement. 

Sano PhD Student

Project title: Gene Therapy using Computational Analytics Approach

Publication date: 7.07.2022

Closing date: 28.07.2022

Level of education: Master's degree

Hours: 40 hours per week

Salary indication: up to 8000 PLN gross monthly

Supervisors:

Sano: Clinical Data Science Research Group Leader

Project start: August 2022 (depends on Candidate’s availability)

Computational Drug Analytics is a rich area of research that has become extremely important during the COVID-19 global pandemic. This project strives to develop a novel algorithm for monitoring cell reprogramming that leverages single-cell multi-omics data, ontology, epigenetics factors, and cell heterogeneity, enabling a more holistic view of the regulatory mechanisms at cellular resolution.

The main activities planned within this project involve the following:

• Computational biology and gene sequencing
• Biological Modeling and Simulations
• Ontology-based Information Extraction of PubMed and clinical trials
• Text analysis and mining
• Network construction, analysis, community detection
• The design of novel algorithms and computational methods
• Integration with multi-omics data sources (e.g., PubChem)
• Proficiency in Python programming and Jupiter notebook and others (Julia, R)

Sano PhD Student

Project title: Applications of machine learning and deep learning in medical imaging and digital pathology

Publication date: 4.07.2022

Closing date: 1.08.2022

Level of education: Master's degree

Hours: 40 hours per week

Salary indication: up to 8000 PLN gross monthly

Supervisors:

Sano: Dr. Arkadiusz Sitek

Project start: August 2022

Degree Awarding Institution: AGH

Imaging technology used in medicine made enormous progress in recent decades and is now commonly used to detect, diagnose, and monitor almost all diseases. With increasing sophistication of the technology the amount of data being produced in medical imaging is staggering. Despite the progress in technology and the quality of imaging data being produced, the interpretation is still done predominantly by radiologists - an approach that has not significantly changed in decades. All healthcare systems experience a shortage of qualified radiologists. Substantial workloads contribute to potential misinterpretations, long waiting times for results, radiologist burnouts, etc.

The goal of the thesis is to develop machine learning techniques that would assist radiologists in their work. This includes worklist prioritization, image quality improvements, automatic interpretation, missed/incidental findings, automatic measurements, etc. Multimodal machine learning, deep learning, radiomics, and classical image and signal processing algorithms will be used. This work will be done with a close collaboration with radiologists and/or other physicians who will advise on clinical significance of the project.