The Health Applications Society focuses on the topics of health applications, with the aim of identifying current and potential problems and contributions to their solutions; to lead in the development, dissemination, and implementation of knowledge and advancing the basic and applied research technologies on health applications.




Log in to see this information

Either the content you're seeking doesn't exist or it requires proper authentication before viewing.


  • San Francisco, California, Working from our San Francisco location and reporting to the Head of Quality Assurance, the QA Engineer will effectively collaborate and  partner with departments across SmartLabs sites. The QA Engineer will own and support the construction validation efforts for our GMP facilities including mechanical, electrical, consumables, and automation for successful development of validation protocol and reports in compliance with all federal, state, and local regulations.    Successful candidates will be able to tackle problems, reduce risk, prioritize their workload in a fast-paced, high-growth environment while always presenting a professional demeanor.  Fast and frequent change is considered normal here, so the ideal candidate will be able to change direction and shift gears while maintaining a high level of productivity.  The QA Engineer will leverage experience in engineering and quality management to bring operational efficiencies and excellence to our members.    In this role you will:   Ensure compliance with the site validation master plan and assist with facility start-up operations documentation.  Lead and champion proactive identification and resolution of technical and compliance issues/gaps.   Provide QA oversight to all Technical Transfers, Aseptic Process Validations and Process Performance Qualifications, as well as QA support to process and analytical changes and other engineering activities (including process/analytical lifecycle management), to ensure successful execution and documentation.   Support Commissioning, Qualification and Validation lifecycle activities related to facility, instruments, equipment, processes and methods.    Oversee the validation plans, qualification protocols, and associated reports and procedures where applicable, as well as calibration/maintenance programs.   Provide QA oversight to the conception, design, execution and commissioning and qualification/validation of major capital projects in support of MAB, Cell Gene Therapy GMP operations at all SmartLabs sites.  Act as QA representation on project steering teams to review and approve complex and/or technically-engineering oriented documentation, and issue resolution.   Provides appropriate support through the QA Engineering team to technical investigations requiring complex root cause analysis and resolution efforts (i.e., CAPAs)  Ensure adherence to internal procedures and industry/regulatory expectations within scope of responsibility, including assurance of facility/equipment controls and release before, during and after production operations   Create, revise, develop, implement, and manage processes to ensure the required specifications for quality, function, and reliability are met.  Maintain compliance with FDA GMP, EMEA cGMP, ISO 9001, and ISO 13485 standards.   Bachelor’s degree with focus in mechanical, electrical, biomedical engineering or related life science degree. A Master’s Degree in Engineering is preferred.  Minimum of 5 years of experience working in engineering, quality and/or life science process development.  Prior experience with FDA regulations and ISO, cGMP, QMS standards is highly preferred.  Excellent organizational skills and attention to detail.  Previous success managing a for-profit laboratory, academic, clinical or pharma environment.  Strong analytical and problem-solving skills   Knowledge in statistical analysis, DOE, impact assessment, root cause analysis, and risk management/FMEA.  Experience engaging in and/or leading Design Reviews.  Effective communication skills and ability to work collaboratively across all levels within a global, multidisciplinary team, including written and verbal communication.  Knowledge of cGMP regulations, and automation standards from relevant health authorities (e.g., FDA, EMA) including all guidelines applicable to biologics, cell and gene therapy, as well as ATMP Regulations.   Capable of recognizing and resolving Quality issues, particularly of a technical nature; informs management of proposed solutions. Seeks management guidance on complex issues; develops procedures.   Familiar with automation requirements/guidance (GAMP 5, ISA Standards, etc.) and validation lifecycle for relevant manufacturing and QC equipment and instrumentation, as well as GMP software and electronic systems (local and enterprise).   Ability to manage documentation including requirements, block diagrams, specifications, cost analysis, engineering analysis, drawings, fluidic schematics.   Detail oriented, with strong GMP, Quality and pharmaceutical Engineering experience.   Manage challenging situations and recommend effective solutions to problems.  Effectively manage multiple tasks.  Effectively collaborate and communicate with internal and external teams, executive management, and clients.  
  • South Korea, Graduate School of Data Science (GSDS) and Department of Industrial & Systems Engineering (ISysE) at KAIST invites applications for tenure-track faculty positions at the levels of Associate/Assistant/Full Professor . KAIST GSDS is a recently established graduate (MS and PhD) program, prepared by a joint team of KAIST faculty with the lead of ISysE department. We are actively seeking candidates who are genuinely interested in building a strong graduate program on data science, defining the future of manufacturing/service industries and/or the human- centric engineering field. In this term of recruit, we would like to invite the following areas: Data science theories and foundations in data science (including AI and machine learning) optimization for data science probabilistic / stochastic model for data science data driven decision making under uncertainty data science + X: applications of data science to solving industrial or social problems, including (but not limited to) manufacturing, financial services, medical and healthcare services, legal services, public services such as social welfare, and so on Manufacturing systems engineering for 2050 : shaping manufacturing systems for 2050: beyond lean production efficient, flexible, disturbance tolerant, agile, and reliable manufacturing system operation management for autonomous production system key enabling technology components for “genuine” industry 4.0 Human-centric engineering data/information visualization, human-computer interaction, human factors, ergonomics, cognitive engineering,  human-integrated  systems,  or  relevant  fields  with  strong theoretical background and first-hand experiences in evaluation techniques (either quantitative or qualitative) application of human-related knowledge to real-world problems, particularly in data- inundating fields Other emerging fields relevant to industrial & systems engineering and data science. Industrial or academic experience will be considered preferably, and students who are expected to complete their PhDs within 9 months from the application date will also be considered. Application documents along with an up-to-date CV should be sent to: Professor Hayong Shin Department of Industrial & Systems Engineering, KAIST Email: hyshin@kaist.ac.kr   Applications are considered on a rolling basis (reviewed each month) until the positions are filled. We strongly recommend applying at your earliest convenience. If you have further inquiries regarding this faculty position announcement such as targeting areas, you may contact Prof. Hayong Shin at hyshin@kaist.ac.kr. ----- KAIST (Korea Advanced Institute of Science and Technology) is a globally renowned science and technology institution, particularly well known for its excellence in engineering and technology. The institute is dedicated to promoting a vibrant academic culture and offers an internationally-minded environment through ways such as teaching all courses in English. You can find more about KAIST at   http://kaist.ac.kr Existing graduate program called “Knowledge Service Engineering (KSE)” was renovated into GSDS with newly defined direction, curriculum, and name. From organizational point of view, GSDS belongs to ISysE faculty. KAIST GSDS is chosen by NRF (research funding agency of Korean government) for a strong financial support for the next 7 years. For general information about the Department of Industrial & Systems Engineering at KAIST, please visit http://ie.kaist.ac.kr and also http://kse.kaist.ac.kr  
  • Menlo Park, California, Meta Platforms, Inc. (f/k/a Facebook, Inc.) has the following position in Menlo Park, CA.   Program Manager:  Work closely with Facebook’s Global Operations team to analyze and improve the health of its products. Telecommute from anywhere in the U.S. permitted (remote work benefit). (ref. code REQ-2205-113295).   For full information & to apply online, visit us at the following website  https://www.metacareers.com/jobs   & search using the ref code(s) above.
  • Linthicum Heights, Maryland, The Healthcare Data Scientist role will join our talented Advanced Data Science & Consulting Services group at the University of Maryland Medical System (UMMS) in support of its strategic portfolio of novel and innovative solutions and services. The successful candidate will have 3+ years of experience with the above listed domains and a passion for working with healthcare data and problem sets. Previous experience with various computational approaches along with an ability to demonstrate a portfolio of relevant prior projects is essential. This role will primarily focus on opportunities and problems sets involving Operation Research - Mathemtical Optimization, Simulation, and Machine Learning. This position will report to the Principal Data Scientist. Will engage in creating problem solving using Machine Learning, Artificial Intelligence, and Operations Research - Mathematical Optimization and Simulation. Anticipates data and science-related bottlenecks, provides escalation management, anticipates and makes trade-offs, and balances clinical and business needs versus scientific and technical constraints. Partners with clinical and business stakeholders in the development of inference-driven features. Actively identifies existing and new features, which could benefit from predictive modeling and implementation of predictive models. Actively identifies and resolves strategic issues that may impair the team’s ability to meet strategic, scientific, and technical goals. Partners with stakeholders to create, maintain, and prioritize the hypothesis and experimentation backlog. Takes large, scientifically complex projects and break them down into manageable hypothesis and experiments to inform, functional specifications, then deliver features in a successful and timely manner. Develops and manages predictive (machine learning and deep learning) and prescriptive (mathematical optimization and simulation) analytic models in support of the organization’s clinical, operations and business initiatives and priorities. Deploys solutions so that they provide actionable insights to the organization and are embedded or integrated with application systems. Support and drive analytic efforts designed around organization’s strategic priorities and clinical/business problems. Builds and extends our analytics portfolio supported by robust documentation. Works with autonomy to find solutions to complex problems using open source tools and in-house development Stays abreast of state-of-the-art literature in the fields of operations research, statistical modeling, mathematical optimization, simulation, machine learning and simulation. Works with the analytics team and clinical/business stakeholders to develop pilots so that they may be tested and validated in pilot/incubator settings . Assists senior leadership with strategies for scaling successful projects across the organization and enhances the analytics applications based on feedback from end-users and clinical/business consumers. Develops strategic, tactical and operational presentations that summarize the results of predictive and prescriptive analytics projects in support of robust strategies for the organization. Ability to formulate and solve complex mathematical optimization problems using exact and heuristic approaches. Ability to develop complex process models using discrete-event-simulation. Proven programming skills in Python; ability and experience to participate in software platform and web application development. Proven communications skills – Effective at working independently and in collaboration with other staff members. Capable of artful storytelling and clearly presenting findings in oral and written format and through graphics. Proven analytical skills – Able to compare, contrast, and validate work with keen attention to detail. Skilled in working with “real world” data including scrubbing, transformation, and imputation. Master’s degree in industrial engineering, computer science, applied mathematics, physics, engineering, or a related field required; PhD degree highly preferred. Extensive work experience and prior proven experience in the desired technical thought leadership may be substituted for education. Strong background in computer science, operations research, industrial & systems engineering statistics or a physical engineering discipline. 3+ years of Machine Learning/Artificial Intelligence, Operations Research - mathematical optimization & simulation, etc. Proven prior experience with Python and R is a must (experience with tools such as WEKA, RapidMiner, or other open source tools are strongly preferred). Ability to develop and apply computational algorithms and AI methods to healthcare data (including, but not limited to data from electronic medical record, business transaction systems, and supply chain). Proven prior experience in developing and deploying healthcare-relevant predictive and prescriptive models. Proven prior practical experience with formulating and solving mathematical (deterministic and stochastic) optimization problems and simulation; prior experience in Arena, FlexSim or similar environments. Experience with discrete-event-simulation preferred. Proven experience with SQL. Proven experience and strong development skills in Python. Proven experience with combining analytic methods and advanced data visualizations. Expert ability to break down and clearly define problems.
  • Silver Spring, Maryland, INTRODUCTION: The Center for Devices and Radiological Health (CDRH or Center) , as the scientific and regulatory component of the U.S. Food and Drug Administration ( FDA ) charged with facilitating and ensuring medical device innovation, safety, and effectiveness, and advancing regulatory science is now accepting applications for a Staff Fellow (Senior Data Scientist) to serve in the Office of Clinical Evidence and Analysis (OCEA or Office) .   OCEA oversees the application of modern artificial intelligence tools, including machine learning and deep learning methodologies, that can be evaluated, piloted, and implemented at scale by CDRH to help the Center evaluate clinical evidence and other device-related data to more efficiently conduct regulatory review activities in support of the Center’s mission.   POSITION SUMMARY:   OCEA is seeking a Staff Fellow (Senior Data Scientist) to develop, pilot, and implement various data analytics tools within CDRH, while collaborating with a team of Data Scientists, across the Office and Center and interface with contractors to accomplish these goals.  The Staff Fellow will support of OCEA’s mission to provide policy and program support regarding clinical trials, biostatistics, real-world evidence, epidemiological analysis, as well as outreach and collaboration with hospital systems and other external stakeholders, to ensure the safety, effectiveness, and reliability of regulated medical devices.    DUTIES / RESPONSIBILITIES: As a Staff Fellow (Senior Data Scientists), the selected candidate will: Serve as an expert and technical authority on analytical and programming techniques necessary to collect, organize, analyze, and interpret unique and highly specialized data sets. Provide subject matter expertise and regulatory support in the form of consultation in the reviews of new medical devices and accompanying test data and reports. Solve complex analytical problems using quantitative approaches. Lead cross-functional teams, which includes product owners, designers, developers, researchers, and content editors, to develop data-driven solutions to address business and user challenges Communicate data findings to stakeholders using different visual formats to picture and provide reports. Provide technical expertise to product teams in the development, implementation, and oversight of new technologies.   PROFESSIONAL EXPERIENCE / KEY REQUIREMENTS: To qualify for this position, you must demonstrate in your resume the necessary experience for this position, which is equivalent to the following: Demonstrated skill in developing artificial intelligence tools Expertise in using open-source programming languages such as Python to manipulate and analyze data Ability to utilize predictive modeling concepts, machine learning (ML) approaches, and/or optimization algorithms to analyze data. Experience with training ML models under data-starved conditions Experience with domain adaptation methods Previous expertise in one or more of ML, deep learning (CNNs, RNNs, LSTMs, GANs), and familiarity with deep learning libraries (TensorFlow, PyTorch, etc.) BASIC QUALIFICATIONS: This position is multidisciplinary, and applicants will be required to meet the specific qualification requirements of the following applicable occupational series: Computer Science Series, 1550 ; Electrical Engineering Series, 0850 ; Bioengineering and Biomedical Engineering Series, 0858 ; General Engineering Series, 0801 ; General Mathematics and Statistics Series, 1501 ; Statistics Series, 1530 ; Mathematical Statistics Series, 1529 ; or other related or a quantitative science field. ADDITIONAL QUALIFICATIONS: At a minimum, the candidate must possess a doctoral-level degree from an accredited institution of higher learning, to include: Ph.D., M.D., D.V.M., D.D.S., D.M.D., Sc.D., or other research doctoral-degree widely recognized in U.S. academe as equivalent to a Ph.D.  Candidates must have professional experience and stature in their area of expertise commensurate with the duties of the scientific position being filled. FOREIGN EDUCATION: If you are using education completed in foreign colleges or universities to meet the qualification requirements, you must show that the education credentials have been evaluated by a private organization that specializes in interpretation of foreign education programs and such education has been deemed equivalent to that gained in an accredited U.S. education program; or full credit has been given for the courses at a U.S. accredited college or university. For further information, visit the U.S. Department of Education website for Foreign Education Evaluation .   CONDITIONS OF EMPLOYMENT: One-year probationary period may be required. This position is for a two (2) year appointment and will be filled through FDA’s Staff Fellowship Program Background and/or Security investigation Applicants who are U.S. Citizens and born male, on (or after) 12/31/1959, must be registered with the Selective Service System OR have an approved This position may require financial disclosure reporting and will be subject to FDA's prohibited financial interest regulation. If you are hired, you may be required to divest of certain financial interests. You are advised to seek additional information on this requirement from the hiring official before accepting any job offers. For additional information, please visit the FDA Ethics and Integrity Office SALARY: Salary is commensurate with education and experience. LOCATION: Silver Spring, Maryland, FDA Headquarters, White Oak Campus How to Apply:  Submit an electronic resume or curriculum vitae, cover letter containing describing why you are uniquely qualified for this position, and a copy of unofficial transcripts all in one document ( Adobe PDF ) to CDRHRecruitment@fda.hhs.gov , with Job Reference code “2022-OCEA-DCEA II- SR Data Scientist-001” in the subject line. Applications will be accepted through July 22, 2022.     Additional Announcement Information   COVID-19:  Due to COVID-19, the Agency is currently in an expanded telework posture. If selected, you may be expected to temporarily telework, even if your home is located outside the local commuting area. Once employees are permitted to return to the office, you will be expected to report to the duty station listed on this announcement within 45 days. At that time, you may be eligible to request to continue to telework one or more days a pay period depending upon the terms of the agency's telework policy. As required by Executive Order 14043, Federal executive branch employees are required to be fully vaccinated against COVID-19 regardless of the employee's duty location or work arrangement (e.g., telework, remote work, etc.), subject to such exceptions as required by law. If selected, you will be required to be vaccinated against COVID-19 and will receive instructions on how to provide documentation.   Security and Background Requirements : All candidates must meet applicable security requirements which include a background check and a minimum of 3 out of the past 5 years’ residency status in the US. If not previously completed, a background security investigation will be required for all appointees. Appointment will be subject to the applicant’s successful completion of a background security investigation and favorable adjudication. Failure to successfully meet these requirements may be grounds for appropriate personnel action. In addition, if hired, a background security reinvestigation or supplemental investigation may be required at a later time. Applicants are also advised that all information concerning qualifications is subject to investigation. False representation may be grounds for non-consideration, non-selection, or appropriate disciplinary Benefits: The Federal Government offers a comprehensive benefits Explore the major benefits offered to most Federal employees at https://www.usa.gov/benefits-for-federal-employees Travel, transportation and relocation expenses will not be paid.   HHS/FDA is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.   DEPARTMENT OF HEALTH AND HUMAN SERVICES IS AN EQUAL OPPORTUNITY EMPLOYER SMOKE FREE ENVIRONMENT SALARY: Salary is commensurate with education and experience.

Latest Discussions

There are no discussions to which you have access

Either the content you're seeking doesn't exist or it requires proper authentication before viewing.

Recent Shared Files

No Data Found

Either the content you're seeking doesn't exist or it requires proper authentication before viewing.


  • photo not available
    Qiushi Chen
    37 Points
  • photo not available
    Hadi El-Amine
    32 Points
  • photo not available
    Ruiwei Jiang
    27 Points