The Postdoctoral Researcher is expected to focus on one of the following areas:
Artificial Intelligence for (1) atmospheric and environmental sciences, (2) Internet of Things (IoT) and sensing technologies, (3) automatic big data analytics, and (4) engineering applications (e.g., condition-based maintenance and renewable energies). Priority will be given to applicants whose expertise can further strengthen and expand the group's research in engineering applications.
AI is transforming sciences and industries, with use cases spanning Predictive Modeling, Computer Vision (CV), and Natural Language Processing (NLP). While AI applications typically rely on cloud infrastructure and powerful GPUs, this project focuses on deploying AI algorithms on resource-constrained embedded devices such as ESP32, Raspberry Pi, Nvidia Jetson Nano, and Vision AI DevKit.
The project explores real-time applications, including digital twinning, vehicle counting, and voice-based sentiment analysis. AI models may be trained in the Microsoft Azure Cloud and deployed to edge devices, ensuring efficient and localized processing. For example, our newly funded project aims at generating real-time dynamic air quality information. Thus, we plan to equip a mobile robot with comprehensive air quality sensors and a camera to navigate construction sites. The camera will capture images and videos to facilitate real-time vehicle counting. Computer vision algorithms will be deployed on an edge device to process the footage and count vehicles on-site. The vehicle count data will complement measurements from aerosol and gas sensors, enhancing the accuracy and depth of air quality assessments.
This position is ideal for a current Master's student, offering the potential to evolve into a thesis project. Future directions could involve testing AI models across diverse edge hardware and refining more advanced algorithms.
Intern 1: IoT Prototype Development
The intern is expected to establish an IoT prototype using Thunderboard Sense 2
Sensor kits and a Raspberry Pi. The sensors measure a set of variables such as temperature and humidity. The aim is to (i) develop/improve the hardware/software codes, (ii) stream the data to a cloud server, (iii) test 20 sensor kits, validate their measurements against a reference instrument, (iv) and return a final report.
Research group: IRON (https://www.helsinki.fi/iron) and 6Gresearch (https://www.helsinki.fi/en/networks/6g-research)
Supervisors/Contact persons: Naser Hossein Motlagh (naser.motlagh@helsinki.fi) and Martha Arbayani Zaidan (martha.zaidan@helsinki.fi)
More information: The topic requires good electronic and programming skills. A nice opportunity to learn!
Intern 2: Building Sensor Data Analytics
The intern will explore a large real-world sensor data collected from an indoor space. The student is expected to implement methods to (i) perform data visualization, (ii) identify sensor locations/coordinates, (iii) improve/suggest new sensor locations, (iv) compare the performance of different sensor deployment settings, and (iv) return a final report.
Research group: IRON (https://www.helsinki.fi/iron) and 6Gresearch (https://www.helsinki.fi/en/networks/6g-research)
Supervisors/Contact persons: Naser Hossein Motlagh (naser.motlagh@helsinki.fi) and Martha Arbayani Zaidan (martha.zaidan@helsinki.fi)
More information: The topic requires good data analytics and visualization skills for example using Python. There is a high chance of continuing for master's thesis!
Mobile devices have emerged as one of the main instruments for tracking the movement of people through the use of device-embedded motion sensors. By capturing detailed data about movement, i.e., acceleration and rotation of the device, useful information can be extracted. Thus, this information can be used to recognize physical activities and phenomena and can serve a wide variety of use cases.
For example, the Transportation Mode Discovery (TMD) using mobile devices, i.e., simple motion sensors such as accelerometers, gyroscopes, and magnetometers can contribute to a large variety of applications such as smart mobility and activity tracking. Currently, detecting different motorized transport modes is difficult and is not supported by standard activity tracking API such as Google’s Activity Recognition API. Therefore, in this thesis topic we aim to i) develop state-of-the-art method(s) for TMD, ii) implement the method(s) using existing datasets (or collecting new datasets), and iii) evaluate the performance of the developed method(s) against the existing studies in the literature.
The candidate will be employed full-time for the duration of six months and will be paid based on the salary system of the University of Helsinki. If you are interested in the topic, for more information please contact Dr. Naser Motlagh (naser.motlagh@helsinki.fi).
Institute for Atmospheric and Earth System Research (INAR) of the Faculty of Science are seeking a DOCTORAL RESEARCHER in AI for enhancing sensing and scientific instrumentation for the project of Artificial Intelligence systems for enhancing sensing technologies and scientific discoveries.
The Doctoral Researcher will work on a project funded by the Academy of Finland. The project aims to develop data science and Artificial Intelligence (AI) based methods to identify and analyze anomalous and drifted data from atmospheric and environmental measurements. Automatic methods will then detect, isolate, and identify the drifted data and/or the faults in scientific instruments. The main goals are to ensure high data quality generation, increase the quality of instrument diagnostics, minimize measurement downtime (I.e., minimize missing data), and reduce engineer workloads in maintaining continuous measurements. The project mainly uses data sets generated from several field campaigns and big data sets generated via the Stations for Measuring Ecosystem-Atmosphere Relations (SMEAR stations) and other related research infrastructure, such as ACTRIS, etc.
The hired candidate will have an opportunity to interact and collaborate with world-class atmospheric scientists in the Institute for Atmospheric and Earth System Research (INAR) and industries, as well as top scientists at the Department of Computer Science (CS), University of Helsinki.
Position description
The doctoral researcher position will discuss actively with experimentalists to gather information on technical problems (which often occur in field campaigns and/or continuous measurements) and then collect potential data sets to be used in the research. Based on the identified technical problems, the doctoral researcher will develop data science methods, such as anomaly detection and machine learning, to automate the process of fault and data drift detection, isolation, and identification.
The position will require the doctoral researcher to advance research in specific technological areas, such as data analytics, artificial intelligence, sensing, and instrumentation. The doctoral researcher will be encouraged to design their own research project within the scope of the overall project in collaboration with the Principal Investigators (PIs). High cooperation between the doctoral researcher and scientists in CS and INAR is a key requirement for the project's success. The successful candidate will be primarily supervised by Dr. Martha Arbayani Zaidan, Prof. Tareq Hussein, and Prof. Tuukka Petäjä. The position will be a fully funded contract for 3 years with a possibility of extension for a fourth year.
Requirements and eligibility criteria
A successful candidate should have a master's degree in atmospheric and/or environmental sciences, electrical engineering, mechanical engineering, or a related field. The candidate must have scientific curiosity and a meticulous work ethic. Based on the position of interest, prior experience in data sciences, sensing and measurements, instrumentation designs and development is highly desirable. A good track record of previous and relevant scientific publications will be considered a big plus. The candidate must have good organizational and time management skills and be able to work both independently and as part of a team. Excellent communication skills in English, both verbal and written, are expected. The University of Helsinki seeks to promote an equitable and inclusive working environment and welcomes applicants from diverse genders, linguistic and cultural backgrounds.
Applicants who do not currently hold a doctoral study right in the Doctoral Programme in Computer Science (DoCS) at the University of Helsinki are eligible to apply, but in the event of hiring, they are expected to acquire the status during the standard 6-month probationary period. Please check the admission periods and eligibility criteria to DoCS: https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-programmes/doctoral-school-and-doctoral-programmes/doctoral-programmes-natural-sciences/doctoral-programme-computer-science/admissions-doctoral-studies.
Salary and benefits
The starting salary of a doctoral researcher is typically 2531-2662 euros/month, depending on previous qualifications and experience.
The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The University provides support for internationally recruited employees with their transition to work and life in Finland. For more on the University of Helsinki as an employer, please see https://www.helsinki.fi/en/about-us/careers.
How to apply
Please submit your application by clicking "Apply now" on the bottom right side of this page. Please submit in a single PDF file in English, which should include the following documents:
A motivation letter describing why you are the ideal candidate for this role (max. 2 pages)
A curriculum vitae (max. 2 pages) including a list of publications (if any).
Names and contact information of two referees, who are willing to provide reference letters upon request (optional).
We aim to fill the position as soon as possible and therefore encourage early applications. However, the latest deadline for submitting applications is October 31th, 2023.
More information
For project and position related questions, please contact
Dr. Martha Arbayani Zaidan, martha.zaidan(at)helsinki.fi
For support with the recruitment system, please contact
HR Specialist Laura Karppinen (laura.karppinen(at)helsinki.fi.
*****
The University of Helsinki (https://www.helsinki.fi/en) is an international scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities in Europe and ranks among the top 100 international universities in the world. We are an equal opportunity employer and offer an attractive and diverse workplace in an inspiring environment with a variety of development opportunities and benefits.
As a part of the Faculty of Science, the Department of Computer Science (https://www.helsinki.fi/en/computer-science) is a leading unit in Finland in its area and responsible for the teaching and research in computer science at the University of Helsinki. The number of professors at the department has grown in recent years and there are now 32 professorships. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive international collaboration with companies and universities. Within teaching, the department’s professors and staff are in charge of the Bachelor’s, Master’s, and Doctoral Programmes in Computer Science, as well as the separate Master’s Programme in Data Science, in which other departments also participate.
The Department of Computer Science (CS) of the Faculty of Science is seeking a DOCTORAL RESEARCHER in AI for big scientific data processing and analytics for the project of Artificial Intelligence systems for enhancing sensing technologies and scientific discoveries.
The Doctoral Researcher will work on a project funded by the Academy of Finland. The project will be carried out in close collaboration with the Institute for Atmospheric and Earth System Research (INAR). The project aims to develop Artificial Intelligence (AI) and data science methods to automate the data processing and analysis of big atmospheric and environmental data, mainly generated via the Stations for Measuring Ecosystem-Atmosphere Relations (SMEAR stations) and other related research infrastructure, such as ACTRIS, etc. The developed methods will be deployed in various platforms, such as computing clusters operated by CSC – IT Center for Science (CSC). The hired candidate will have an opportunity to interact and collaborate with world-class atmospheric scientists in INAR, data scientists and data engineers in CSC, top scientists at the Department of Computer Science (CS), and many other collaborators within Atmosphere and Climate Competence Center (ACCC) and Finnish Center for Artificial Intelligence (FCAI).
Position description
The doctoral researcher position will focus on researching, designing, and developing various feature engineering, machine learning (ML), and deep learning (DL) methods. The ML/DL models are developed mainly based on time-series measurements gathered at many research infrastructures, such as SMEAR stations. Other data sets can be in the forms of spatiotemporal database, images and other unstructured data sets. The developed ML/DL models are expected to be deployed on our computing platforms (e.g., CSC etc.) to process the gathered measurement data and generate the results automatically in near real-time.
The position will require the doctoral researcher to advance research in specific technological areas, such as supervised and unsupervised machine learning, deep learning, computer vision, and cloud computing. The doctoral researcher will be encouraged to design their own research project within the scope of the overall project in collaboration with the Principal Investigators (PIs). High cooperation between the doctoral researcher and scientists in CS and INAR is a key requirement for the project's success. The successful candidate will be primarily supervised by Dr. Martha Arbayani Zaidan, Prof. Tuukka Petäjä and Prof. Sasu Tarkoma. The position will be a fully funded contract for 3 years with a possibility of extension for a fourth year.
Requirements and eligibility criteria
A successful candidate should have a master's degree in computer science, electrical engineering, or a related field. The candidate must have scientific curiosity and a meticulous work ethic. Based on the position of interest, prior experience in data sciences, AI, data engineering, cloud computing, and/or their deployments is desirable. A good track record of relevant scientific publications will be considered a plus. The candidate must have good organizational and time management skills and be able to work both independently and as part of a team. Excellent communication skills in English, both verbal and written, are expected. The University of Helsinki seeks to promote an equitable and inclusive working environment and welcomes applicants from diverse genders, linguistic and cultural backgrounds.
Applicants who do not currently hold a doctoral study right in the Doctoral Programme in Computer Science (DoCS) at the University of Helsinki are eligible to apply, but in the event of hiring, they are expected to acquire the status during the standard 6-month probationary period. Please check the admission periods and eligibility criteria to DoCS: https://www.helsinki.fi/en/admissions-and-education/apply-doctoral-programmes/doctoral-school-and-doctoral-programmes/doctoral-programmes-natural-sciences/doctoral-programme-computer-science/admissions-doctoral-studies.
Salary and benefits
The starting salary of a doctoral researcher is typically 2531-2662 euros/month, depending on previous qualifications and experience.
The University of Helsinki offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The University provides support for internationally recruited employees with their transition to work and life in Finland. For more on the University of Helsinki as an employer, please see https://www.helsinki.fi/en/about-us/careers.
How to apply
Please submit your application by clicking "Apply now" on the bottom right side of this page. Please submit in a single PDF file in English, which should including the following documents:
We aim to fill the position as soon as possible and therefore encourage early applications. However, the latest deadline for submitting applications is October 31st, 2023.
More information
For project and position related questions, please contact
For support with the recruitment system, please contact
*****
The University of Helsinki (https://www.helsinki.fi/en) is an international scientific community of 40,000 students and researchers. It is one of the leading multidisciplinary research universities in Europe and ranks among the top 100 international universities in the world. We are an equal opportunity employer and offer an attractive and diverse workplace in an inspiring environment with a variety of development opportunities and benefits.
As a part of the Faculty of Science, the Department of Computer Science (https://www.helsinki.fi/en/computer-science) is a leading unit in Finland in its area and responsible for the teaching and research in computer science at the University of Helsinki. The number of professors at the department has grown in recent years and there are now 32 professorships. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed, intelligent, and interactive systems, networks, security, and software and database systems. The department has extensive international collaboration with companies and universities. Within teaching, the department’s professors and staff are in charge of the Bachelor’s, Master’s, and Doctoral Programmes in Computer Science, as well as the separate Master’s Programme in Data Science, in which other departments also participate.
Martha Zaidan delivered two guest lectures on "AI Technologies for Enhancing Sensor Networks: Accuracy, Reliability, and Autonomy" in:
The groups below where the IRON leaders are also actively involved.
The Finnish research flagships below where the IRON leaders are also actively involved.