Job Openings at African Population And Health Research Center (APHRC)

Duties/Responsibilities

The Mathematical Modeler will be responsible for creating models that demonstrate complex processes for solving health-related problems. They will leverage existing data resources within and beyond APHRC and use their skills combined with software technology to support effective health decision making.

The Mathematical Modeler will:

• Develop and adapt/modify existing mathematical models including deterministic, stochastic, network and individual or agent-based models for health outcomes;
• Work closely with DSE data scientists and AI software developers/engineer to design efficient programs, algorithms, or systems to reduce programming time for parameter sampling, model fitting (to data), and analyses;
• Import and export large sets of raw and synthetic data files for use in statistical analysis and machine learning;
• Manipulate, transform, encrypt, and combine data from multiple data sets including data at the APHRC micro portal, INSPIRE platform and other administrative data sources;
• Perform analytical (counterfactual) simulation exercises using mathematical models for various health outcomes at APHRC;
• Perform literature reviews supported by domain experts, researchers and epidemiologists, to identify model parameters;
• Perform descriptive and exploratory statistical analysis of individual-level or aggregate-level data to parameterize transmission models;
• Validate code and models to ensure algorithms are complete, reproducible, accurate and of high quality prior to analysis;
• Maintain high quality coding practices, version control, and documentation of coding for reproducibility;
• Develop standard operating procedures for effective mathematical modeling activities at DSE;
• Communicate and liaise with research, policy, program, and community partners including coordinating and chairing collaborator meetings;
• Contribute to report and manuscript writing, knowledge translation products, grants, and ethics review board applications;
• Prepare tables, figures, and reports for end-users, including clinicians, researchers, community-based organizations, public health decision-makers;
• Train, mentor, and DSE staff interested in mathematical modeling; and
• Work with internal and international collaborators on modelling projects.

Qualifications, Skills, and Experience 

• Master’s degree in Mathematical Epidemiology, Applied Mathematics, Epidemiology, Statistics, Computer Science or other related field. Holders of Bachelor’s degrees with relevant experience will also be considered.
• At least three years’ relevant experience in modelling systems and/or numerical methods.
• Experience in mathematical dynamic modelling of infectious disease transmission, PK modelling, Non-linear models or agent-based models.
• Experience with economic analyses / economic evaluations / health-economics is an asset.
• Must be fully proficient in the use of R, Python.
• Ability to manage computer programming activities and support analytic operations.
• Experience in Frequentist and Bayesian statistics, and likelihoods.
• Experience with machine-learning and data visualization tools.
• Experience in basic statistical analysis, modelling or scientific computing.
• Good communication skills to describe findings to both technical and non-technical audiences.
• Excellent problem-solving skills, has attention to detail and a strong analytical mind.
• Demonstrates ability to work both independently and to work collaboratively with internal and external team members, and stakeholders.
• Ability to multi-task, work accurately and effectively to deadlines; has good self-assessment of timing of tasks and ability to set deadlines. Organizational and time management skills to manage and prioritize workload.
• Demonstrate an appreciation of technical and analytic challenges, and learning new approaches and topics.

Closing: November 05, 2022

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Duties/Responsibilities

The Data Scientist will be responsible for using novel data science tools including machine learning (ML) and artificial intelligence (AI) to address APHRC’s research questions. They will be expected to expand the use of advanced analytics and data science in the DSE and APHRC.

The Data Scientist will:

• Identify data sources for research needs, compile, collect, very relevant structured and unstructured data for analysis;
• Building Machine Learning and predictive models, ML algorithms to address data-driven research questions;
• Apply pre-processing steps including feature engineering, model selection, training and tuning for effective results;
• Work closely with data engineers, managers to produce data in to usable formats;
• Analyze data for trends and patterns, and find answers to specific questions;
• Set up data infrastructure, develop, implement and maintain databases;
• Generate information and insights from data sets, and identify trends and patterns;
• Prepare and support monthly reports and scientific publications;
• Create visualizations of data from the Center e.g. research generated data on micro portal;
• Train DSE members in robust data science techniques; and
• Contribute to report and manuscript writing, knowledge translation products, grants, and ethics review board applications.

Qualifications, Skills, and Experience 

• PhD in data science, applied mathematics, computational science and engineering, applied statistics or other related field. A master’s degree in any of the following mathematics, statistics or computer science.
• A minimum of seven years of professional experience in data analytics, computer science or statistics; with at least one year’s postdoctoral experience.
• Programming skills. Knowledge of statistical programming languages like R, Python, and database query languages like SQL, Oracle, Hive, Pig is desirable. Familiarity with Scala, Java, or C++is an added advantage.
• Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators, etc. Proficiency in statistics is essential for data-driven activities. 
• Machine learning. Good knowledge of machine learning methods like k-Nearest Neighbors, Naive Bayes, SVM, Decision Forests is essential.
• Strong math skills (Multivariable Calculus and Linear Algebra) to support predictive performance or algorithm optimization techniques. 
• Data wrangling. Proficiency in handling imperfections in data is a critical aspect of this role. 
• Experience with data visualization tools like R shiny, matplotlib, ggplot, d3.js.ArcGIS, QGIS, PowerBi, Excel, Tableau to visually encode data and generation of dashboards for interpretation.
• Good communication skills to describe findings to both technical and non-technical audiences.
• Excellent problem-solving skills, has attention to detail and a strong analytical mind.
• Demonstrates ability to work both independently and to work collaboratively with internal and external team members, and stakeholders.
• Ability to multi-task, work accurately and effectively to deadlines; has good self-assessment of timing of tasks and ability to set deadlines; have organizational and time management skills to manage and prioritize workload.
• Demonstrate an appreciation of technical and analytic challenges, and learning new approaches and topics.

Closing: December 31, 2022

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Duties/Responsibilities

The AI Software Engineer will be responsible for creating deployable versions of all Machine Learning models and integration of these into products for improving health and well-being. They will join APHRC’s multidisciplinary team to help in shaping new strategy and showcasing the potential for AI through early-stage solutions.

The AI Software Engineer will:

• Develop ML models alongside DSE’s data engineers, data analysts, data scientists and provide provide end to end AI solutions;
• Build Code Infrastructure from ML models developed by data scientists in DSE using advanced technologies;
• Package ML models into usable products by researches and policy makers;
• Create End Point APIs from the ML algorithms. These will include products such mobile applications, web services, chatbots, CDSS etc.;
• Develop the development of platform for data sharing;
• Provide updates on breakthrough artificial intelligence technologies with the potential to transform the Center’s research environment, the research staff or policy makers’ experience and influence policy development and decision making;
• Work closely with DSE data engineers, program and data managers to produce data into usable formats for analysis;
• Prepare and support monthly reports and scientific publications;
• Support data managers in the use of the metadata software programs;
• Develop training curricula and training materials;
• Attend DSE technical and progress meetings; and
• Contribute to report and manuscript writing, knowledge translation products, grants, and ethics review board applications.

Qualifications, Skills, and Experience 

• PhD in Data science, Applied Mathematics, Computational Science and Engineering, Applied Statistics. Master’s degree in Computer Science, Data Science, Software Development, or other related field.
• At least three years of experience formulating and strategizing AI solutions; with at least one-year’s postdoctoral experience.
• Solid understanding of common programming languages used in AI, such as Python, Java, C++, and R.
• Advanced knowledge of statistical and algorithmic models as well as of fundamental mathematical concepts, such as linear algebra and probability.
• Experience working with large data sets and writing efficient code capable of processing large data streams at speed.
• Proven experience in applying AI to practical and all-inclusive technology solutions.
• Hands-on knowledge in machine learning, deep learning, Tensorflow, Python, NLP.
• Understanding of functional design principles, object-oriented programming principles, basic algorithms.
• Expertise in REST API development, NoSQL design, RDBMS design.
• Proven expertise in using deep learning, neuro-linguistic programming (NLP), computer vision, chatbots, and robotics to help the internal teams promote diverse research outcomes and drive innovation is a must have.
• Understanding of website scripts such as XML, Javascript, JSON.
• Understanding of ETL framework and ETL tools including Alteryx and Microsoft SSIS.
• Digital marketing analytics tools including Google 360, Google Analytics, Google Tag Manager and Adobe Marketing Suite.
• Experience with data visualization tools like R shiny, matplotlib, ggplot, d3.js.ArcGIS, QGIS, Tableau to visually encode data and generation of dashboards for interpretation.
• Good communication skills to describe findings to both technical and non-technical audiences.
• Excellent problem-solving skills, self-driven, has attention to detail with a strong analytical mind.
• Demonstrate ability to work both independently and to work collaboratively with internal and external team members, and stakeholders.
• Ability to multi-task, work accurately and effectively to deadlines; has good self-assessment of timing of tasks and ability to set deadlines. Organizational and time management skills to manage and prioritize workload.
• Demonstrate an appreciation of technical and analytic challenges, and learning new approaches and topics.

Closing: December 31, 2022