CHPC-NITheCS Coding Summer School 2023

30 January 2023 – 10 February 2023

The Centre for High Performance Computing (CHPC) and the National Institute for Theoretical and Computational Sciences (NITheCS) are organizing a coding summer school that offers introductions to Foundations of Theoretical and Computational Sciences on topics such as Data Visualization, Data Analysis, Modelling and Simulation, Stochastic Methods, Machine Learning and Software Management.

A basic programming course that introduces participants to Linux (Ubuntu) command line and bash scripting, and the Python programming language will be given as a foundational tool for the school.

Students registered for Honours, Masters and PhD studies as well as postdoc fellows, in South Africa are eligible to apply and the attendance is free of charge. The school will take on a physical form at various university locations around the country, therefore participants will be required to attend one of the university locations.

The University of the Western Cape will provide one of these locations on its campus, and all interested candidates are encouraged to apply.

Course content

  • Daily lectures and interactive tutorials
  • Moodle used as the learning management environment
  • PDF notes, exercises, and YouTube videos provided
  • Zoom used for live streaming
  • Slack used as official communication medium
  • Prizes awarded to select students

Requirements and Registration

Participants are encouraged to bring their own laptops but where it is not possible, the organizers might assist to access an on-site computer. No programming skills and basic Linux knowledge are required, although that would be an advantage. Applications can be done at this registration link and more information on the can be obtained here.

Important dates

  • Closing date for registration: Saturday, 31 December 2022
  • Notification of successful candidates: by 16 January 2023
  • School start and orientation: Monday, 30 January 2023
  • School end: Friday, 10 February 2023

Africa Open Science Hardware Summit

AfricaOSH is an organisation that aims to inspire African makers, and is focused on open source scientific tools and hardware. They seeks to promote and provide a platform for innovation and creation in Africa, and hold annual events.

The 2022 annual summit theme is Growing the Do-It-Yourself & Do-It-Together (DIY/DIT) Culture for Community Transformation : a focus on Open Health, and promises to be insightful, educative, innovative and fun. The event will be hosted by MboaLab and take place from 29 September-1 October in Yaounde, Cameroon. Read more about it here.

Applications to attend the 2022 AfricaOSH annual summit are now open:

ilifu-supported Africa CDC course at SANBI

SANBI are currently teaching a course on SARS-CoV-2 (COVID-19) bioinformatics to visitors from public health labs across Africa. The course is taking place at the University of the Western Cape from the 23 to 27 May 2022, and is using ilifu, South Africa’s big data infrastructure for data-intensive research. 

Africa CDC aims to strengthen capacities and capabilities at public health institutions in Africa in order to detect and respond quickly and effectively to disease threats and outbreaks. They have data-driven interventions and programmes, and SANBI has been working with Africa CDC since 2018. 

In 2020, the Africa CDC launched its Institute of Pathogen Genomics (IPG), which has been at the forefront of supporting SARS-CoV-2 sequencing on the African continent. SANBI is one of the specialist centres assisting Africa CDC in its work developing pathogen genomics and bioinformatics. As part of this role, they are running a week-long course on SARS-CoV-2 sequence analysis for people from public health labs in 9 African countries – Morocco (Institut Pasteur du Maroc), Egypt (Central Public Health Laboratory), Ethiopia (Ethiopian Public Health Institute), Uganda (Center Public Health Institute), Kenya (National Public Health Laboratory), Senegal (Institut Pasteur de Dakar), Zambia (Zambian National Public Health Institute), Ghana (Noguchi Memorial Institute for Medical Research) and South Africa (National Institute for Communicable Diseases). Nigeria (Nigeria CDC) and DRC (Institut National de Recherche Biomédicale) could not attend in-person, but are participating online. 

Back row (L-R): Ziphozakhe Mashologu, Wael Saif, Harris Onywera, Peter van Heusden, Alan Christoffels, Leonard Kingwara, Ayitewala Alisen, Abebe Negeri, Abdelmajid Eloualid, Amadou Diallo. Front row (L-R) Susan Alicia Fernol, Michelle Lowe, Annie Chan, Tracey Calvert-Joshua, Quaneeta Mohktar, Francis Ahiakpah, Moussa Diagne. Not present: Mpanga Kasonde, Akil Prince, Emmanuel Lokilo . 

SANBI have been ilifu partners since its inception, and Peter van Heusden, Senior Bioinformatician at SANBI, is one of the organisers of the workshop. He says that participants have found it to be “an excellent resource to support public health bioinformatics”. ilifu is a node in the South African national data infrastructure which enables South African researchers to be leaders in the strategic science domains of astronomy and bioinformatics. 

Course participants working on data analysis in SANBI’s Aaron Klug seminar room, 23 May 2022.

The training relies on cloud infrastructure provided by Ilifu – each lab gets their own installation of SANBI’s SARS-CoV-2 Workbench to work on, and gets hands-on experience with uploading data, doing data analysis and visualising their results. While the current training has focused on SARS-CoV-2, the discussions have ranged across a number of other infectious diseases that these public health labs are responding to: HIV, TB, hepatitis, malaria, influenza and other pathogens. SANBI sees this training as feeding into Africa CDC’s efforts to build a Community of Practice in public health bioinformatics and genomic surveillance.

Training Opportunity : Data Science and Machine Learning

A training opportunity for data science and machine learning is available and registration closes on 25 May.
Makerere University School of Public Health (MakSPH) in Kampala, Uganda, is working in partnership with four other African universities to research the COVID-19 response in Africa. Through the collaboration, a community of practice (COP) has been establised. It is aimed at developing the capacity of African institutions to prepare, analyse and respond to disease epidemics successfully.
As part of the COP, and in partnership with IBM Research Africa (IBMRA) scientists, who have expertise in artificial intelligence (AI), data science, and machine learning, the project has organised a capacity-building opportunity on data science and machine learning.
Participants interested in or with a background in data science, artificial intelligence, machine learning and cloud computing are encouraged to register. There is no minimum skill requirement aside from computer literacy.

Topics that will be covered include analysing the impact of COVID-19 on essential health services using time series analysis; learning from COVID-19 models to support what-if scenario analysis; and intervention planning and descriptive statistics to analyse NPIs implemented in African countries.

The training will be conducted online through Webex, with an expected engagement of about 2 hours every week. Facilitation will be in both English and French, and the programme will run until October 2022.

Interested participants can register here
by 25 May 2022.

Africa Women in Data Science: Online Event

DARA Big Data (Development in Africa through Radio Astronomy), in partnership with the Office of Astronomy for Development (OAD), IDIA (Inter-University Institute for Data Intensive Astronomy) and SARAO (South African Radio Astronomy Observatory) is hosting a free 3-day Africa Women in Data Science online event. The event will coincide with International Women’s Day 2022 and will also mark the one year anniversary of the publication of the SARAO Women in Data Science report.

The event organisers hope to help build a thriving African community of female data scientists and promote skills development for women who are interested data science careers. Registration for the event closes January 31 2022.

The event will take place from 8-10 March 2022, which coincides with International Women’s Day. It aims to increase African women’s participation in the 4th Industrial Revolution (4IR) to build a prosperous, resilient Africa of the future. The integral role of African women for the 4IR will be discussed and various opportunities will be showcased for young women hoping to get into the field of data science.

Africa Women in Data Science is free to attend and will be split into a conference on Day 1 (March 8) and a hackathon on Days 2 and 3 (March 9-10). The conference will feature inspiring female panel discussions, presentations from leading industry experts and question and answer sessions. Day 1 is open to anyone across Africa with a keen interest in data science. To register for the conference, only complete the first section of the registration form.

Register here:

Enquiries can be emailed to

Using machine learning for food quality and safety assurance

The latest research published by eResearch Office’s Dr Frederic Isingizwe on detecting defects in fresh agri-food products dealt with detecting soft damage to apple fruit while they are still invisible to the naked eye.

Damage to fresh agri-food products due to brute impact or compression force can occur during handling and transport, can be invisible at an early stage but becomes more pronounced with time, either in the consumer’s hands or on a retailer’s shelf. Such damage to fresh produce accelerates the deterioration of fruit and vegetables and can facilitate infections by micro-organisms, which makes products unsafe to consume.

The research was conducted to aid with sorting and grading fresh products, either at an industrial or smaller scale. We demonstrated that these invisible defects can be detected using shortwave hyperspectral imaging techniques and by using machine learning algorithms, we established the degree to which the differentiation of defective from sound apple fruits is feasible.

Read more about this work here.

eWorkshop: Command Line Interface for Genomics Beginners

Forensic DNA Lab UWC

UWC’s Forensic DNA Lab (FDL) hosted an eWorkshop (online workshop) on using the Command Line Interface, Unix, shell and other tools for genomics.

The course was aimed at graduate students and research scientists who will work with genomic and bioinformatic datasets for the first time and ran from 10thJune to 15thJuly in two hours weekly sessions.

Seventeen (17) participants were registered, including staff, Honours, Masters and PhD students from different institutions including the South African Biodiversity Institute; University of the Western Cape; Stellenbosch University; University of Johannesburg; University of Pavia (Italy) and ICGEB/UCT.

More about the eWorkshop

Command line interface (CLI) and graphic user interface (GUI) are different ways of interacting with a computer. The CLI ‘is a text-based interface used to interact with software and operating system by typing commands into the interface and receive a response in the same way’. The GUI on the other hand, is a visual-based interface featuring the use of graphic images such as windows, icons and menus, and is navigated mostly using a mouse and the keyboard sometimes.

The CLI is important for proficiency in genomics as most bioinformatics tools use the shell and have no graphical interface. Importantly, CLI is essential for using remote high performance computing centers e.g. ILIFU, CHPC.

The course was designed to impart the following knowledge and skills to the participants:

  1. Discuss practical differences between Unix and Windows;
  2. Navigate and manipulate files and folders using standard bash commands;
  3. Write basic scripts for bash including piping between commands;
  4. Access the ILIFU HPC and submit simple scripts to SLURM; and
  5. Discuss folder/directory structure for genomic projects.

The ilifu cluster computing infrastructure was used for training tasks, which included lessons on basic Unix bash commands and practical activities which required specialised Singularity containerized software.

X-ray Observations Supporting MIGHTEE MeerKAT Science Project Unveiled

New X-ray map reveals the growing supermassive black holes in next-generation MeerKAT survey fields 

One of the largest X-ray surveys using the European Space Agency’s XMM-Newton space observatory has mapped nearly 12,000 X-ray sources across three large, prime regions of the sky. The X-ray sources represent active galactic nuclei and galaxy clusters, and the survey captures the growth of the supermassive black holes at the cores of these galaxies. This X-ray survey complements previous X-ray surveys, allowing the researchers to map active galactic nuclei in a wide range of cosmic environments.

The XMM-SERVS survey lays key groundwork for studying the cosmic history and physical  properties of active galaxies 

Figure 1: XMM-Newton image of the 4.6-square-degree W-CDF-S field reveals the wide, sensitive view of the X-ray sky provided by XMM-SERVS. The detected sources, most of which are growing supermassive black holes, are color coded according to the energies of the X rays detected (with red having the lowest energies and blue the highest). The white outline indicates the area of the Chandra Deep Field-South, a well-known ultradeep pencil-beam X ray survey. The image highlights how XMM-SERVS has now provided sensitive panoramic X ray imaging around this survey. The XMM-Newton image covers an area about 20 times larger than the apparent size of the full moon, shown to scale at upper left.
Figure 2: XMM-Newton image of the 3.2-square-degree ELAIS-S1 field, which is about 15 times larger than the apparent size of the full moon (shown to scale at lower right). XMM SERVS provides a wide, sensitive X-ray view of this region.

These X-ray observations will be invaluable to study the active galactic nuclei (i.e. black holes) and galaxy clusters (the largest cosmic structures bound together by gravity) detected by the MIGHTEE MeerKAT Large Survey Project (led by UWC Visiting Professor Matt Jarvis and UWC Research Chair Russ Taylor) in its ongoing mission to study the faint radio sky.

Qingling Ni and W. Niel Brandt from Penn State presented the results of the XMM-Spitzer  Extragalactic Representative Volume Survey (XMM-SERVS) at a press briefing during the 238th meeting of the American Astronomical  Society on 7 June. A paper describing the survey, authored by an international team of astronomers including UWC’s eResearch Director Prof Mattia Vaccari, has been accepted for publication in The Astrophysical Journal Supplement. A pre-print is also available on

“X-ray surveys are the best way to find growing supermassive black holes, which are located at  the cores of many large galaxies,” said Ni, a graduate student at Penn State and lead author of  the paper. “With this massive new survey, we can access population data about growing  supermassive black holes to better understand their physical properties and evolution over cosmic history.” 

“This survey represents key foundational work upon which, I suspect, hundreds of studies will  be built over the next decade or two,” said Brandt, Verne M. Willaman Professor of Astronomy  and Astrophysics and professor of physics at Penn State, and one of the leaders of the study.  “XMM-Newton was the best mission to gather these data, and we needed to invest a lot of  observation time for this study—with a total combined exposure of nearly 60 days—because it  will be so important for active galaxy studies, galaxy cluster studies, and for understanding  large-scale structures in the universe. It required a multiyear, multinational effort and it’s  incredibly gratifying to get it done. We are most grateful to the European Space Agency and  NASA for their long-term support of this work.” 

Caption from featured image: XMM-Newton image of the 5.3-square-degree XMM-LSS field, which is about 25 times  larger than the apparent size of the full moon (shown to scale at lower right). XMM-LSS was the  first XMM-SERVS field to have been observed by XMM-Newton. Chien-Ting Chen, a former postdoctoral researcher at Penn State who is now an astronomer at USRA, led the work for this  field (see Chen et al. 2018, Mon. Not. Roy. Ast. Soc.). XMM-SERVS provides a wide, sensitive X ray view of this region

eWorkshop: Command Line Interface for Genomics Beginners

Forensic DNA Lab UWC

The Forensic DNA Lab (FDL, UWC) will be running an eWorkshop (online workshop) on using the Command Line Interface, Unix, shell and other tools for genomics. 

The course will run from 10 June to 15 July with once a week lessons.  The course is aimed at graduate students and research scientists who will work with genomic and bioinformatic datasets for the first time. We will help attendees get started in using the CLI for performing genomic workflows. Attendees require no previous experience in CLI tools.

More about the eWorkshop

Command line interface (CLI) and graphic user interface (GUI) are different ways of interacting with a computer’s operating system. The CLI allows you to control your computer using commands entered with a keyboard instead of controlling graphical user interfaces (GUIs) with a mouse/keyboard combination.

The CLI is important for proficiency in genomics as most bioinformatics tools use the shell and have no graphical interface. Importantly, CLI is essential for using remote high performance computing centers e.g. ILIFU, CHPC.

After the course, participants should be able to:

  1. Discuss practical differences between Unix and Windows;
  2. Navigate and manipulate files and folders using standard bash commands;
  3. Write basic scripts for bash including piping between commands;
  4. Access the ILIFU HPC and submit simple scripts to SLURM; and
  5. Discuss folder/directory structure for genomic projects.

The course registration is now closed.

Research Opportunity Announcement: Data Generation Projects for the Bridge to Artificial Intelligence (Bridge2AI) Program

The NIH (US National Institute of Health) Common Fund’s Bridge to Artificial Intelligence (Bridge2AI) program is designed to help propel biomedical research forward by setting the stage for widespread adoption of artificial intelligence (AI) and machine learning (ML) that tackles complex biomedical challenges beyond human intuition. It is a new NIH Common Fund program, and will tap into the power of AI to lead the way toward insights that can ultimately inform clinical decisions and individualize care. AI, which encompasses many methods, including modern machine learning (ML), offers potential solutions to many challenges in biomedical and behavioral research.

The Bridge2AI program plans to support several interdisciplinary Data Generation Projects (OTA-21-008) and one complementary cross-cutting Integration, Dissemination and Evaluation (BRIDGE) Center (NOT-RM-21-021) to generate flagship data sets and best practices for the collection and preparation of AI/ML-ready data to address biomedical and behavioral research grand challenges. 

It also plans to support the formation of teams richly diverse in perspectives, backgrounds, and academic and technical disciplines. The current Research Opportunity Announcement (ROA) for Data Generation Projects for the Bridge to Artificial Intelligence (Bridge2AI) Program (OT2) (OTA-21-008) requires a Plan for Enhancing Diverse Perspectives (PEDP)—a summary of strategies to advance the scientific and technical merit of the proposed project(s) through inclusivity. Visit the Bridge2AI Program Resources page and Program FAQs for additional information on building diverse teams and for PEDP guidance.    To facilitate team building across communities and ensure responsiveness of proposals, NIH strongly encourages potential proposers to participate in the Grand Challenge Team Building Activities taking place in June 2021, please save the date for these upcoming events:    

Bridge2AI Program Town Hall
June 9, 2021
2:00-3:30pm ET
Bridge2AI Data Generation Project Module Microlabs
June 14, 16, and 18, 2021
2:00-4:00pm ET each day
Bridge2AI Grand Challenge Team Building Expo
June 23, 2021
11:00am-5:00pm ET

Further information about how to register and participate in these events, as well as an online networking platform, will be coming soon. Please check the Bridge2AI Scientific Meetings page for updates.    Please refer to the research opportunity announcement (OTA-21-008) for additional information on application submission and review. A Letter of Intent (LOI) is required, LOIs must be emailed to by 11:59 PM ET on or before July 20, 2021.   We encourage you to share the Bridge2AI listserv signup with your contacts and networks so they will receive updates on future funding announcements and the latest news from the Bridge2AI program. You can also keep up to date with the latest information by visiting the Bridge2AIwebsite. Questions can be sent to

Read more about the vision for this new program in a recent NLM Director’s blog