Applications are invited for the Positions of Research Assistant and Research Associate in the following Projects under the Sino-Pak Center for Artificial Intelligence, PAF-IAST.

Terms and Conditions:

  • The applicant(s) should make the payment proof in the form of Bank deposit slips/Online transfer Slip of Rs.500/ in the bank account titled "Establishment of Sino-Pak Center for Artificial Intelligence" maintained at National Bank of Pakistan, PAK Austria Branch Haripur, A/C No. 2330-3166367407 or IBAN PK85 NBPA 2330 0031 6636 7407.
  • The last date for receipt of the online applications and attested copies of all the supporting documents uploaded at relevant areas is 25- Jul- 2021.
  • A person who intends to apply for more than one position shall apply separately for each position. The applicant can apply for maximum 3 positions.
  • Any error or omission in advertisement or details shall be subject to rectification by the Institute.
  • PAF-IAST reserves the right to increase or decrease the number of positions as per provision in the PC-1 or cancel the appointment of any or all positions without assigning any reason.


Scientific Field(s): AI, Data Science, Forecasting
Primary Goals: Develop an AI-based forecasting tool that provides accurate forecasts of the solar energy specific to the region and geographical coordinates in Pakistan

Abstract

With all the technological advancements, it is hard to think of a world with a limited electrical energy supply. The world is moving towards clean generation systems empowered by renewable energy (RE) resources, intending to achieve sustainability. Among RE resources, solar energy is the most emerging one and has gained massive attention in recent decades. Renewable energy production is greatly influenced by climate parameters, which fluctuate significantly and cause surges in power generation. Integration of such fluctuating power sources into the systems may create penetrations that impact the planning of utilities and stability of the system. To alleviate significant losses through the effective integration of variable solar power sources, short-term solar irradiance forecasting plays a pivotal role. However, existing AI-based approaches have been designed for region-specific data. While regional solar irradiance data of Pakistan remains unexplored to date. We will develop an AI-Engine that can be utilized for solar irradiance prediction of multi-region data. AI engine will have a pool of diverse feature engineering approaches along with multiple newly designed autoencoders to learn an effective representation of input data. Further reduced feature space will be passed to a pool of Machine Learning (ML) and Deep Learning (DL) based regressors that will predict solar irradiance. Our AI engine will use an optimized way to select different parameters of ML and DL-based regressors. Finally, by using training data, the AI engine will provide us best end-to-end system with the appropriate combination of different approaches for particular region data.

S # Job Description Apply
1

Research Assistant

No. of Positions:04, Fixed salary Rs.55,000/- per month, Duration: Up-to 01-Year

Bachelor’s degree in Electrical/Electronics Computer/Software/Telecom/Mechatronics Engineering or similar discipline with at least 1 years of experience of R & D projects in industry/academia in the area of Deep Learning/Machine Learning OR MS (course work completed/in progress) in Electrical/Electronics/Computer/ Software/ Telecom/ Mechatronics Engineering or similar discipline with hands-on experience in Speech processing /Deep Learning/Machine Learning

Job requirements include:

  • Good oral and written communication skills
  • Strong understanding of Machine Learning, Dimensionality reduction approaches
  • Strong understanding of Deep Learning, Autoencoders
  • Strong understanding of Deep Learning, CNN, and LSTM based regressors.
  • Excellent programming skills in Python and deep learning platforms for data processing, visualization, and modeling (Numpy, Pandas, Matplotlib/Seaborn, Keras, Pytorch).
  • Research paper writing for top-tier conferences and Journals.
  • Report writing for the project

Apply Now
2

Research Associate

No. of Positions:01, Fixed salary Rs.80,000/- per month, Duration: 2 months

Bachelor’s degree in Electrical, Computer/Software, Mechatronics, Electronics Engineering or Computer Science or similar discipline with at least 3 years of experience of R & D projects in industry/academia in the area of Computer Vision/Deep Learning/Machine Learning OR MS in Electrical, Computer/Software, Electronics Engineering or Computer Science or similar discipline with at least 1 year of experience of R & D projects in industry/academia in the area of Computer Vision/Deep Learning/Machine Learning

Preference will be given to candidates having:

  • Good Oral and written communication skills
  • Strong understanding of Machine Learning and Deep Learning
  • Excellent programming skills in Python (for data processing, visualization, and modeling.
  • Expert in Deep learning (autoencoders)
  • Report writing for the project

Apply Now


Scientific Field(s): AI, Forecasting, Energy Informatics, Renewable Energy, Power Systems
Primary Goals: The goal of this project is to develop and test a prototype energy management system for buildings that minimize the cost of energy and ensure the availability of the energy supply. It is assumed that a PV system and storage have been installed at the building.

Abstract

A reliable and cost-effective electricity supply is pivotal for the advancement of society, sustainable economy, and wellbeing of its citizens. INTERACT project aims to deliver an intelligent and cost-optimal solution for energy management for the building equipped with PV and energy storage. This project shall consist of a forecasting module and a controller. The forecasting module shall predict the building load intelligently and dynamically. Similarly, the PV power forecasting module shall also have a self-correcting mechanism to deal with the modeling issues. The third variable that adds novelty to the project is the estimation of the power available from the grid. These forecast variables shall drive the optimal dispatch of the energy storage to meet the building load in the most cost economical way and also according to the user preferences. The first part of the controller development shall be to perform mathematical modeling of the problem. Subsequently, the problem shall be convexified to find a deterministic solution to the optimization problem. The forecast module along with the controller model shall be deployed on a prototype in the laboratory environment. The industrial partner shall be responsible for communicating the field requirements, deploying the controller in the field, and debugging practical issues. The innovative approach shall provide flexibility to the building operator in reducing its energy costs and also to ensure the availability of power during the defined intervals. INTERACT shall lead to a comprehensive and adaptable solution to the energy problem in Pakistan.

S # Job Description Apply
1

Research Assistant

No. of Positions:02, Fixed salary Rs.55,000/- per month, Duration: Up-to 01-Year

EMS controller design and prototyping:

Bachelor’s degree in Electrical/Electronics Computer/Software/Telecom/Mechatronics Engineering or similar discipline with at least 1 years of experience of R & D projects in industry/academia in embedded system, power system, and controller design OR MS (course work completed/in progress) ) in Electrical/Electronics/ Computer/ Software/ Telecom/Mechatronics Engineering or similar discipline with hands-on experience in embedded system, power system, and controller design.

Job requirements include:

  • Good oral and written communication skills
  • Strong understanding of statistical modeling related to energy forecasting.
  • Excellent programming skills in Python and optimization libraries like Pyomo.
  • Experience in deploying the controller on Raspberry Pi and debugging experience.
  • System integration that involves PV, energy storage, and load.
  • Research paper writing for top-tier conferences and Journals.
  • Report writing for the project

Apply Now
2

Research Associate

No. of Positions:01, Fixed salary Rs.80,000/- per month, Duration: 4 months

Bachelor’s degree in Electrical, Computer/Software, Mechatronics, Electronics Engineering or Computer Science or similar discipline with at least 3 years of experience of R & D projects in industry/academia in the area of Computer Vision/Deep Learning/Machine Learning OR MS in Electrical, Computer/Software, Electronics Engineering or Computer Science or similar discipline with at least 1 year of experience of R & D projects in industry/academia in the area of Computer Vision/Deep Learning/Machine Learning

Job requirements include:

  • Good Oral and written communication skills
  • Strong understanding of statistical modeling related to energy forecasting.
  • Excellent programming skills in Python (for data processing, feature extraction, visualization, modeling (Numpy, Pandas, Matplotlib) and optimization libraries like Pyomo
  • Strong understanding of the machine and deep learning with application in forecasting algorithms
  • Experience in deploying the software on Raspberry-Pi
  • Research paper writing for top-tier conferences and Journals
  • Report writing for the project

Apply Now


Scientific Field(s): Artificial Intelligence, Computer Vision
Primary Goals: The proposed IntelliSurv system targets the development of an intelligent add-on in surveillance systems through the deployment of AI-on-the-Edge technology for anomaly detection in real-time videos. The IntelliSurv will be a groundbreaking indigenous R&D catering to the national security (street crimes in particular) needs of the country. Sino-Pak Center for Artificial Intelligence and the project team aim to provide a viable solution to the law enforcement agencies thus will be helpful in their capacity building and immediate mobilization of emergency response units.

Abstract

Security has always been a problem for developing countries like Pakistan and street crimes are one of the key factors in security-related challenges. Law enforcement agencies have already been in search of different technological solutions to detect street crimes and other anomalies on immediate notice for prompt action. Therefore, developing an intelligent surveillance system for video anomaly detection is a pressing need. Surveillance systems have become increasingly popular in the globalization process. However, even after the deployment of huge CCTV infrastructures, the full involvement of human operators in traditional surveillance systems has led to shortcomings. For instance, high labor cost, limited capability for multiple-screen monitoring, inconsistency during long durations, etc. are the key issues. We aim to develop an intelligent surveillance system “IntelliSurv”, for the detection of anomalies in real-time videos. We intend to target street crimes considering them as one of the key anomalies in the CCTV videos. IntelliSurv system will utilize deep neural networks to perform deep video analysis for the detection and tracking of humans from the live videos. Human action detection algorithms will be developed to identify abnormal actions in the videos. The intended algorithms will be deployed on state-of-the-art edge devices to pitch a complete black-box solution for real-time anomaly detection in a realistic environment. As a result, emergency response units can be more effective and efficient to deal with the anomaly. Deployment of IntelliSurv in streets, roads, and campus environments will not only help in the prevention of crimes but will also aid law enforcement agencies to take prompt actions against anomalous events.

S # Job Description Apply
1

Research Assistant

No. of Positions:02, Fixed salary Rs.55,000/- per month, Duration: Up-to 01-Year

Bachelor’s degree in Electrical, Computer/Software, Mechatronics, Electronics Engineering or Computer Science or similar discipline with 1 year of experience of R & D projects in industry/academia in the area of Computer Vision/Deep Learning/ Machine Learning OR MS with course work completed in Electrical, Computer/Software, or Computer Science or similar discipline.

Preference will be given to candidates having:

  • Strong understanding in various areas of Deep Learning, Computer Vision, Machine Learning, Real-Time Image, and Video Processing, AI on the Edge
  • Knowledge and experience of working with third-party and open-source libraries.
  • Fluency in Python stack for data processing, visualization, and modeling (Numpy, Pandas, OpenCV, Matplotlib/Seaborn).
  • Fluency in at least one of the following deep learning frameworks Tensorflow/Pytorch/Keras.
  • Knowledge and experience of various object detection models like Yolo, SSD, FRCNN, etc.
  • Knowledge and experience of various feature extraction methods for videos like C3D, I3D, etc.
  • Working experience in Nvidia GPU
  • Understanding of Linux environment and deployment on cloud and edge devices is required.
  • Good writing skills
  • Job requirements Include:

    • Dataset collection, annotation, clipping, and pre-processing.
    • Researching to find state-of-the-art algorithms that can solve problems with optimal accuracy.
    • Implementing novel algorithms and state-of-the-art methods for human action recognition and detection
    • Design, develop, implement, validate, deploy and maintain complex models using advanced machine learning and deep learning techniques.
    • Building efficient and optimized systems to parallelize operations (e.g. through GPUs) for quick response times.
    • Meet the coding style and standards requirements in python.
    • Deployment of the algorithms on the edge devices e.g. Nvidia Jetson, TX2, Google Coral, etc.
Apply Now
2

Research Associate

No. of Positions:01, Fixed salary Rs.80,000/- per month, Duration: Up-to 01-Year

Bachelor’s degree in Electrical, Computer/Software, Mechatronics, Electronics Engineering or Computer Science or similar discipline with at least 3 years of experience of R & D projects in industry/academia in the area of Computer Vision/Deep Learning/Machine Learning OR MS in Electrical, Computer/Software, Electronics Engineering or Computer Science or similar discipline with at least 1 year of experience of R & D projects in industry/academia in the area of Computer Vision/Deep Learning/Machine Learning

Preference will be given to candidates having:

  • Strong understanding in various areas of Deep Learning, Computer Vision, Machine Learning, Real-Time Image, and Video Processing, AI on the Edge
  • Knowledge and experience of working with third-party and open-source libraries.
  • Fluency in Python stack for data processing, visualization, and modeling (Numpy, Pandas, OpenCV, Matplotlib/Seaborn).
  • Fluency in at least one of the following deep learning frameworks Tensorflow/Pytorch/Keras.
  • Knowledge and experience of various object detection models like Yolo, SSD, FRCNN, etc.
  • Knowledge and experience of various feature extraction methods for videos like C3D, I3D, etc.
  • Working experience in Nvidia GPU
  • Understanding of Linux environment and deployment on cloud and edge devices is required.
  • Good writing skills
  • Job requirements Include:

    • Researching to find algorithms that can solve the problem with optimal accuracy.
    • Researching to find state-of-the-art algorithms that can solve problems with optimal accuracy.
    • Implementing novel algorithms and state-of-the-art methods for human action recognition and detection
    • Design, develop, implement, validate, deploy and maintain complex models using advanced machine learning and deep learning techniques.
    • Building efficient and optimized systems to parallelize operations (e.g. through GPUs) for quick response times.
    • Meet the coding style and standards requirements in python.
    • Deployment of the algorithms on the edge devices e.g. Nvidia Jetson, TX2, Google Coral, etc.
    • Research paper writing for top-tier conferences and Journals.
    • Report writing for the project.
Apply Now


Scientific Field(s): Low-vision rehabilitation, Artificial Intelligence
Primary Goals: To develop a smart rehabilitation solution for Retinal Degenerative Diseases (RDD) based on patient’s visual field specifications (saccades and blind spots) so that they can learn faster utilizing their residual vision.

Abstract

Retinal Degenerative Diseases (RDD) are among the major causes of adult-age blindness and low-vision worldwide. Unfortunately, to date it is not possible to reverse the retinal damage, however, efforts are in progress to slow down the retinal degeneration process and provide rehabilitation to the RDD individuals through certain devices and training programs. The focus of these rehabilitation devices and training programs is to utilize the residual vision and develop a significant Preferred Retinal Locus/loci (PRL). Perceptual Learning (PL) training is shown to bring a positive change in a patient’s life quality, but this training is generalized and does not address an individual’s scotoma and saccade patterns. Can we use Artificial Intelligence (AI) to develop customized PL training for each individual? This project offers a robust, adaptive, and intelligent PL training solution that integrates classical rehabilitation techniques with modern AI technology for clinical applications to improve the quality of life for RDD-affected patients. We aim to use eye-tracking to learn saccade patterns based on an individual’s PRL. Based on these saccade patterns, customized two-dimensional PL exercises will be designed using which subjects can learn to develop strategies to enhance spatial representation skills and develop significant PRL/PRLs. We also aim to use this training data of saccades in 2-D for three-dimensional PL inside a room or by using virtual reality, to develop better strategies for eye movements using PRL in the real world. The use of AI-based PL training can help RDD individuals to rapidly develop an effective PRL that can help them significantly in better understanding of environment and improvement in quality of life.

S # Job Description Apply
1

Research Assistant (Ophthalmology)

No. of Positions:01, Fixed salary Rs.55,000/- per month, Duration: Up-to 01-Year

BS with 1-year relevant experience
OR
MS scholar with course work completed.

Job requirements include:

  • Degree in Medical Sciences or Engineering.
  • Hands-on experience with Ophthalmologists is required
  • Good publication and data analysis skills is preferred.
  • Strong public communication skills.

Apply Now
2

Research Assistant – Data Collection Expert

No. of Positions:01, Fixed salary Rs.55,000/- per month, Duration: Up-to 01-Year

BS with 1-year relevant experience
OR
MS scholar with course work completed.

Job requirements include:

  • Degree in Electrical/ Electronics/ Computer/ Biomedical engineering or relevant fields.
  • Hand-on experience with human data collection in clinics is required
  • Preference will be given to candidates having experience in working with Ophthalmologists.
  • Good publication and data analysis skills is preferred.

Apply Now
3

Research Associate

No. of Positions:01, Fixed salary Rs.80,000/- per month, Duration: Up-to 01-Year

BS with 3-year relevant experience
OR
MS with 1-year relevant experience

Job requirements include:

  • BS in Electrical/ Electronics/ Computer engineering or relevant discipline .
  • MS in Artificial Intelligence/ Deep Learning/ Machine learning/ Computer sciences/ Computer engineering or equivalent.
  • Hands-on experience in the field of Artificial Intelligence, Machine Learning, or deep learning will be preferred.
  • A good publication record will be a plus.

Apply Now


Scientific Field(s): Artificial intelligence, radar-based monitoring, gesture recognition
Primary Goals: The project output is in the form of a production-ready prototype with the following objectives:

  1. To develop a hardware-software framework for obtaining radar data.
  2. To formulate a library of unique gestures suitable for detection using mm-wave radar.
  3. To develop a machine learning pipeline for gesture recognition and classification.
  4. Integrate the radar hardware-software system with public use devices.
  5. To test and customize the product for the use-cases of public interest such as touchless systems and assistive living devices for blind people.
  6. To demonstrate a working system to potential customers on an open day.
  7. To submit research papers in conferences and journals.

Abstract

Gestures are the primary actions that manifest various human expressions, and these manifestations are independent of age, gender, and health conditions. Considering the importance of gestures for communication with the surrounding environment, automatic detection of gestures using the intelligent electronic system is an interesting domain having application in diverse fields. As a fundamental use case, a “touchless” system is an important application of the intelligent electronic gesture recognition approach. A touchless system is effective to communicate with a machine without having physical contact with it, a possible way to avoid the spread of viruses and bacteria such as COVID-19. Depending on the ambient conditions, the SARS CoV-2 virus has been found alive for hours or even days on surfaces, creating a huge risk of transmission through touching of these fomites followed by touching the mouth, nose, or eyes. In public places, these surfaces could range from elevator controls, doorknobs, banks, hospitals & restaurant service counter machines, ATMs, point-of-sale (POS), sanitizing and vending machines, and many more. To prevent surface transmission, touchless sensing, and operation of devices in the above scenarios through micro-gesture recognition (MGR) is a need of the hour. Therefore, this project aims to utilize the latest mm-wave radar technology at 60GHz and augment it with the power of AI to firstly develop a library of micro-gestures and secondly to integrate it with some public use devices to demonstrate touchless sensing.

S # Job Description Apply
1

Research Assistant – Radar & RF

No. of Positions:01, Fixed salary Rs.55,000/- per month, Duration: Up-to 01-Year

BS with 1-year relevant experience
OR
Enrolled MS scholar in a relevant program

Job requirements include:

  • Knowledge of radar, RF & Microwave & antennas.
  • Expertise with configuring radar embedded modules for acquiring data, microcontrollers & microprocessors would be a plus.
  • Experience with MATLAB, Python & C is desirable.

Apply Now
2

Research Assistant – Embedded & Power Electronics

No. of Positions:01, Fixed salary Rs.55,000/- per month, Duration: Up-to 01-Year

BS with 1-year relevant experience
OR
Enrolled MS scholar in a relevant program

Job requirements include:

  • Knowledge of embedded systems and expertise in using microcontrollers & microprocessors in power electronics applications.
  • Working knowledge of elevator systems, ATMs that require human interaction would be a plus.

Apply Now
3

Research Associate - ML & AI

No. of Positions:02, Fixed salary Rs.80,000/- per month, Duration: Up-to 01-Year

BS with 3-year relevant experience
OR
MS with 1-year relevant experience

Job requirements include:

  • Having the experience to lead a project and manage its milestones to report it to principal investigators.
  • Having strong research experience and the ability to write research papers.
  • Having a working knowledge of machine learning techniques for embedded systems such as neural networks and decision trees, SVM, and Bayesian classifiers
  • Good working knowledge of Python: pandas, NumPy, sci-kit learn, scipy, matplotlib, Keras, TensorFlow.
  • Having a good understanding of radar data and identifying patterns in it.
  • Knowing product development process

Apply Now