The Clinical trials Monitor will work closely with the Clinical trials manager and the Team Lead for Internal monitors to ensure that the IDI research monitoring framework is strengthened.
1. Participate in the following monitoring activities of research studies at IDI to ensure compliance with approved study protocols and human participants’ protection: ? Ensure that risk assessment is conducted for the protocols and guide the development of a risk-based monitoring plan. ? Ensure that the study teams are adequately trained on the protocol, background, and relevant SOPs prior to the conduct of any study activities ? Maintain regular communication with the Principal Investigators (PIs) and Study Coordinators (SCs) including scheduling monitoring visits, monitoring recommendations, and their resolution. ? Evaluate conformance to the protocol, protection of human participants’ regulations, pharmacy and laboratory methods, GCP and GCLP ? Verify that the investigator has adequate qualifications and resources that remain adequate throughout the study period and that the study teams and facilities, including laboratories, pharmacy, and equipment, are adequate to safely and properly conduct the study and these remain adequate throughout the study period. ? Verify that the investigator follows the approved protocol and all approved amendments, if any. ? Verify that written informed consent is obtained before each participant's participation in the study. ? Verify that the investigators and the study teams are performing the specified study functions, in accordance with the protocol and any other written agreement between the sponsor and the investigator/institution, and have not delegated these functions to unauthorized individuals. ? Verify that the investigator is enrolling only eligible participants. ? Review the participant screening and enrolment rate and support studies accordingly. ? Verify that source data, documents, and or CRF, other study records are accurate, legible, contemporaneous, original, attributable, and complete. Additionally, verify that source data is in correspondence with the data on the CRFs and database successively ? Verify that the investigator provides all the required reports, notifications, applications, and submissions and that these documents are accurate, complete, timely, legible, dated, and properly filed in the regulatory binder to identify the study. ? Ensure that missed visits, tests, and examinations that were not conducted as well as withdrawals and dropouts of enrolled participants are clearly documented on the CRFs and in accordance with the study protocol, SOPs, and manual (s). ? Ensure that appropriate corrections, additions, or deletions are made, dated, explained (if necessary), and initialed by the investigator or by a member of the investigator's trial staff who is authorized to initial CRF changes for the investigator. ? Ensure that all deviations from the protocol, SOPs, manual (s), GCP, and the applicable regulatory requirements are communicated to the investigator with appropriate action to correct the deviation (if possible) and actions designed to prevent the recurrence of the detected deviations. ? Review reports including SAEs, abnormal laboratory values, data QCs, specimen QCs, monthly reports, etc. ? Ensure timely submission of written monitoring reports for review by the Clinical Trials Manager ? Provide approved monitoring reports with the PIs and SCs ? Ensure that recommendations highlighted in monitoring visit reports are addressed in a timely manner ? Participate in development of the Quality Improvement projects based on the recurrent monitoring findings 2. Participate in regular research office and monitor team update check-in meetings. 3. Ensure awareness of updated national and international ethical guidelines 4. Execute any other duties as may reasonably be assigned by the research office.
• A Bachelor’s degree in a health-related subject is required • A master's degree in Public health, Bioethics, and any other related fields are an added advantage • Certified Clinical Research Associate by a recognized body. • A minimum of 3 years of clinical trial monitoring in a busy research institution. • Understanding of clinical trials monitoring frameworks • Demonstrated strong report-writing skills • Pays attention to details • Good oral and written communication skills • Good presentation skills including PowerPoint • Demonstrated initiative and self-management skills • Demonstrated strong problem-solving skills • Demonstrated ability to build and maintain relationships with individuals and teams • Willing to learn and able to work with minimal supervision • Excellent computer skills
Call for applications: Internship for Females at African center of Excellence in Bioinformatics and Data Intensive Sciences
Empowering Uganda’s Women in Health Data Science: Identifying Barriers, Bridging Knowledge and Innovation for Tangible Impact: She Data Science (SHEDS)
Proposed start: June 15th, 2024
The She Data Science (SHEDS) project is pleased to invite suitable applications from females for six internships for the year 2024. SHEDS is a collaborative initiative between the African center of Excellence in Bioinformatics and Data Intensive Sciences, Infectious Diseases Institute, Makerere University, Kampala, Uganda and the Institute of Global Health Sciences (IGHS) at the University of California San Francisco (UCSF), USA.
About the SHEDS program
The increasing adoption of technologies like mobile phones, high throughput genomic sequencing, IoT and electronic health records is accelerating the buildup of an avalanche of data: clinical, genomic, epidemiological, climate-related and social/behavioral data. These growing volumes and complexity of data, render the rapidly expanding field of “Big Data” analysis and interpretation essential to improving health and economic outcomes.
Data Science (DS), which encapsulates Machine Learning and Artificial Intelligence (AI) provides a pathway to the leveraging and enhancement of these data into meaningful and actionable information. However, the highly technical nature of DS as well its powerful potential, simultaneously pause the risk of ‘leaving behind’ sections of the population that have already been disadvantaged. In Uganda in particular, the high gender disparity within STEM fields means that women are more likely to be left behind, resulting in the unintended consequence of DS further widening the gender gap in STEM.
This program is thus going to target the training and advancement of Ugandan women in data science and (or) bioinformatics. It achieves this goal through three critical areas: 1) Skilling women in data science / bioinformatics methods and techniques, 2) identify barriers to women in STEM, Data Science and bioinformatics 3) Providing a bridge to help trainees translate their data science skills into biomedical and public health practice.
Benefits of the program
Internship fields
The interns will work on projects that employ data science, mathematical and (or) bioinformatics to any of the following areas: a) Antimicrobial resistance (AMR) including the design of antimicrobial drug combination therapies, identifying One Health AMR transmission pathways, and utilizing data science methodologies to guide antimicrobial stewardship initiatives; b) Human Genomics including the role of repeats in the human genome; c) cancer including cancer genomics and genomics data science; and d) Natural Language Processing (NLP) and (or) generative AI solutions for health problems.
Submission
Submit the following documents as a single pdf file
NB:
The Business Development Graduate Trainee will support acquisition of new business, further development of existing business, and monitoring programmatic compliance across all the IDI main programs. The Business Development Graduate Trainee will be working under the direct supervision of, and be evaluated by the IDI Manager (Strategic Information and Business Development).
To carry out basic laboratory tests for diagnosis of diseases with focus on Gene Xpert testing and other HIV/AIDS related tests.
Call for applications: Funded Research Year MSc Fellowship Opportunities at Makerere University
Empowering Uganda’s Women in Health Data Science: Identifying Barriers, Bridging Knowledge and Innovation for Tangible Impact: She Data Science (SHEDS)
Call open: May 13th, 2024
Call closes: June 20th, 2024
Proposed start: September 2nd, 2024
The She Data Science (SHEDS) project is pleased to invite suitable applications from females for two fully funded PhD fellowships for the year 2024. SHEDS is a collaborative initiative between the African center of Excellence in Bioinformatics and Data Intensive Sciences, Infectious Diseases Institute, Makerere University, Kampala, Uganda and the Institute of Global Health Sciences (IGHS) at the University of California San Francisco (UCSF), USA.
About the SHEDS program
The increasing adoption of technologies like mobile phones, high throughput genomic sequencing, IoT and electronic health records is accelerating the buildup of an avalanche of data: clinical, genomic, epidemiological, climate-related and social/behavioral data. These growing volumes and complexity of data, render the rapidly expanding field of “Big Data” analysis and interpretation essential to improving health and economic outcomes.
Data Science (DS), which encapsulates Machine Learning and Artificial Intelligence (AI) provides a pathway to the leveraging and enhancement of these data into meaningful and actionable information. However, the highly technical nature of DS as well its powerful potential, simultaneously pause the risk of ‘leaving behind’ sections of the population that have already been disadvantaged. In Uganda in particular, the high gender disparity within STEM fields means that women are more likely to be left behind, resulting in the unintended consequence of DS further widening the gender gap in STEM.
This program is thus going to target the training and advancement of Ugandan women in data science and (or) bioinformatics. It achieves this goal through three critical areas: 1) Skilling women in data science / bioinformatics methods and techniques, 2) identify barriers to women in STEM, Data Science and bioinformatics 3) Providing a bridge to help trainees translate their data science skills into biomedical and public health practice.
Benefits of the program
Research concept
The research concept should be one that employs data science, mathematical and (or) bioinformatics to any of the following areas: a) Antimicrobial resistance (AMR) including the design of antimicrobial drug combination therapies, identifying One Health AMR transmission pathways, and utilizing data science methodologies to guide antimicrobial stewardship initiatives; b) Human Genomics including the role of repeats in the human genome; c) cancer including cancer genomics and genomics data science; and d) Natural Language Processing (NLP) and (or) generative AI solutions for health problems.
Submission
Submit the following documents as a single pdf file
Application deadline: June 20th 2024
NB:
Call for applications: Fully Funded 2-year MSc Fellowship Opportunities at Makerere University
Empowering Uganda’s Women in Health Data Science: Identifying Barriers, Bridging Knowledge and Innovation for Tangible Impact: She Data Science (SHEDS)
Call open: May 13th, 2024
Call closes: June 20th, 2024
Proposed start: September 2nd, 2024
The She Data Science (SHEDS) project is pleased to invite suitable applications from females for two fully funded PhD fellowships for the year 2024. SHEDS is a collaborative initiative between the African center of Excellence in Bioinformatics and Data Intensive Sciences, Infectious Diseases Institute, Makerere University, Kampala, Uganda and the Institute of Global Health Sciences (IGHS) at the University of California San Francisco (UCSF), USA.
About the SHEDS program
The increasing adoption of technologies like mobile phones, high throughput genomic sequencing, IoT and electronic health records is accelerating the buildup of an avalanche of data: clinical, genomic, epidemiological, climate-related and social/behavioral data. These growing volumes and complexity of data, render the rapidly expanding field of “Big Data” analysis and interpretation essential to improving health and economic outcomes.
Data Science (DS), which encapsulates Machine Learning and Artificial Intelligence (AI) provides a pathway to the leveraging and enhancement of these data into meaningful and actionable information. However, the highly technical nature of DS as well its powerful potential, simultaneously pause the risk of ‘leaving behind’ sections of the population that have already been disadvantaged. In Uganda in particular, the high gender disparity within STEM fields means that women are more likely to be left behind, resulting in the unintended consequence of DS further widening the gender gap in STEM.
This program is thus going to target the training and advancement of Ugandan women in data science and (or) bioinformatics. It achieves this goal through three critical areas: 1) Skilling women in data science / bioinformatics methods and techniques, 2) identify barriers to women in STEM, Data Science and bioinformatics 3) Providing a bridge to help trainees translate their data science skills into biomedical and public health practice.
Benefits of the program
Submission
Submit the following documents as a single pdf file
Application deadline: June 20th 2024
NB:
Call for applications: Fully Funded PhD Fellowship Opportunities for Females at Makerere University
Empowering Uganda’s Women in Health Data Science: Identifying Barriers, Bridging Knowledge and Innovation for Tangible Impact: She Data Science (SHEDS)
Call open: May 13th, 2024
Call closes: June 20th, 2024
Proposed start: September 2nd, 2024
The She Data Science (SHEDS) project is pleased to invite suitable applications from females for two fully funded PhD fellowships for the year 2024. SHEDS is a collaborative initiative between the African center of Excellence in Bioinformatics and Data Intensive Sciences(ACE), Infectious Diseases Institute (IDI), Makerere University, Kampala, Uganda and the Institute of Global Health Sciences (IGHS) at the University of California San Francisco (UCSF), USA.
About the SHEDS program
The increasing adoption of technologies like mobile phones, high throughput genomic sequencing, IoT and electronic health records is accelerating the buildup of an avalanche of data: clinical, genomic, epidemiological, climate-related and social/behavioral data. These growing volumes and complexity of data, render the rapidly expanding field of “Big Data” analysis and interpretation essential to improving health and economic outcomes.
Data Science (DS), which encapsulates Machine Learning and Artificial Intelligence (AI) provides a pathway to the leveraging and enhancement of these data into meaningful and actionable information. However, the highly technical nature of DS as well its powerful potential, simultaneously pause the risk of ‘leaving behind’ sections of the population that have already been disadvantaged. In Uganda in particular, the high gender disparity within STEM fields means that women are more likely to be left behind, resulting in the unintended consequence of DS further widening the gender gap in STEM.
This program is thus going to target the training and advancement of Ugandan women in data science and (or) bioinformatics. It achieves this goal through three critical areas: 1) Skilling women in data science / bioinformatics methods and techniques, 2) identify barriers to women in STEM, Data Science and bioinformatics 3) Providing a bridge to help trainees translate their data science skills into biomedical and public health practice.
Benefits of the program
Research concept
The research concept should be one that employs data science, mathematical and (or) bioinformatics to any of the following areas: a) Antimicrobial resistance (AMR) including the design of antimicrobial drug combination therapies, identifying One Health AMR transmission pathways, and utilizing data science methodologies to guide antimicrobial stewardship initiatives; b) Human Genomics including the role of repeats in the human genome; c) cancer including cancer genomics and genomics data science; and d) Natural Language Processing (NLP) and (or) generative AI solutions for health problems.
Submission
Submit the following documents as a single pdf file
Application deadline: June 20th 2024
NB: