Additional qualifications include: • A strong background and expertise in Bayesian statistical ... networks, and/or data and safety monitoring board statistical activities. • Experience ...
Additional qualifications include: • A strong background and expertise in Bayesian statistical ... networks, and/or data and safety monitoring board statistical activities. • Experience ...
Sr Applied ML Engineer - Physics-Driven Systems & Optimization
Harrisonville, NJ · On-site
$103K - $142K/yr
Graph Neural Networks (GNNs) for geometry/topology-aware modeling * Transformers for sequential and ... Bayesian, gradient-based, and gradient-free optimization * Reinforcement Learning (PPO, DDPG, SAC ...
Sr Applied ML Engineer - Physics-Driven Systems & Optimization
Harrisonville, NJ · On-site
$103K - $142K/yr
Graph Neural Networks (GNNs) for geometry/topology-aware modeling * Transformers for sequential and ... Bayesian, gradient-based, and gradient-free optimization * Reinforcement Learning (PPO, DDPG, SAC ...
Senior Data Scientist - Business Innovation
Titusville, NJ · On-site
$109 - $174.80/hr
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub or BitBucket. * Experience in the commercial pharmaceuticals business.
Senior Data Scientist - Business Innovation
Titusville, NJ · On-site
$109 - $174.80/hr
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub or BitBucket. * Experience in the commercial pharmaceuticals business.
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub orBitBucket. * Experience in the commercial pharmaceuticals business.
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub orBitBucket. * Experience in the commercial pharmaceuticals business.
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub or BitBucket. * Experience in the commercial pharmaceuticals business.
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub or BitBucket. * Experience in the commercial pharmaceuticals business.
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub orBitBucket. * Experience in the commercial pharmaceuticals business.
... networks, and/or Bayesian models. * Proficiency with Python and SQL. * Proficient with source control platforms such as GitHub orBitBucket. * Experience in the commercial pharmaceuticals business.
Bayesian Networks information
What is the difference between Bayesian Networks vs Data Analysts?
| Aspect | Bayesian Networks | Data Analysts |
|---|---|---|
| Required Credentials | Statistics, Data Science, Computer Science degrees; certifications in probabilistic modeling | Statistics, Data Science, Business Analytics degrees; certifications in data analysis tools |
| Work Environment | Research, modeling, and algorithm development in tech or research firms | Data interpretation, reporting, and visualization across various industries |
| Industry Usage | Used for probabilistic reasoning, decision support, and machine learning | Used for data interpretation, reporting, and business insights |
Bayesian Networks focus on probabilistic modeling and decision-making algorithms, often requiring advanced statistical knowledge. Data Analysts primarily interpret and visualize data to inform business decisions. While both roles involve data, Bayesian Networks are more technical and model-driven, whereas Data Analysts focus on data interpretation and reporting.
What are Bayesian networks?
Bayesian Networks are probabilistic graphical models that represent a set of variables and their conditional dependencies using a directed acyclic graph. They are used to model uncertainty in complex systems by encoding relationships between variables and allowing for efficient inference and reasoning. These networks are widely applied in fields such as machine learning, diagnostics, decision support, and bioinformatics to help predict outcomes and understand causal relationships.
What are the key skills and qualifications needed to thrive as a Bayesian networks specialist, and why are they important?
To thrive as a Bayesian Networks Specialist, you need a strong background in statistics, probability theory, and machine learning, often supported by a degree in computer science, mathematics, or a related field. Proficiency with programming languages such as Python or R, and experience using specialized libraries like pgmpy or bnlearn, are typically required. Strong analytical thinking, problem-solving ability, and effective communication skills set standout professionals apart in this role. These competencies are crucial for designing, implementing, and interpreting Bayesian models that inform critical decision-making in complex domains.
What are some common challenges faced by professionals working with Bayesian networks in real-world projects?
Professionals working with Bayesian Networks often encounter challenges such as handling incomplete or noisy data, defining accurate conditional dependencies, and ensuring computational efficiency for large or complex networks. Collaboration with domain experts is crucial to correctly structure the network and validate assumptions. Additionally, integrating Bayesian models with existing data systems and effectively communicating probabilistic results to non-technical stakeholders are important aspects of the role.
What are popular job titles related to Bayesian Networks jobs in Philadelphia, PA? For Bayesian Networks jobs in Philadelphia, PA, the most frequently searched job titles are:
- Computer And Information Research Scientist
- Pharmaceutical Data Scientist
- Phd Data Scientist
- Full Time Cannabis Research Scientist
- Pain Research Scientist
- Temporary Research Scientist
- No Experience Research Scientist
- Full Time Remote Data Scientist
- Machine Learning Research Scientist
- Remote Biotech Research Scientist
What job categories do people searching Bayesian Networks jobs in Philadelphia, PA look for? The top searched job categories for Bayesian Networks jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Bayesian Networks jobs? Cities near Philadelphia, PA with the most Bayesian Networks job openings:
Assistant Professor of Epidemiology, Research Track
Philadelphia, PA • On-site
Full-time
Re-posted 26 days ago
University Of Pennsylvania rating
8.1
Based on 81 frontline employees who took The Breakroom Quiz
160th of 617 rated colleges and universities
Job description
Description
The Department of Biostatistics and Epidemiology at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for several Assistant Professor positions in the non-tenure research track. Expertise is required in the specific area of the statistical design and analysis of randomized clinical trials. Applicants must have a Ph.D. or equivalent degree.
Additional qualifications include:
• A strong background and expertise in Bayesian statistical methods, causal inference, machine learning, pragmatic trial designs with cluster-randomization methods, and complex missing data methodology.
• Expertise in statistical programming (R, Python, Stan/BUGS).
• Proficiency with clinical trial simulation to support both methodological research and the initial design and subsequent modification of trials.
• Experience supporting large-scale trials, clinical research networks, and/or data and safety monitoring board statistical activities.
• Experience collaborating with clinician-scientists, particularly physician-scientists.
• Proficiency in analyzing and interpreting patient-reported outcome measures such as quality-of-life endpoints, including handling of missing data such as that due to non-response, death, or other intercurrent events.
• Demonstrated aptitude working with state-of-the-art computing infrastructure, Overleaf/LaTeX, GitHub, and supporting reproducible research pipelines.
Research or scholarship responsibilities may include demonstrated ability to lead peer-reviewed publications in clinical trials methodology and support multi-site collaborative research projects.
The Center for Clinical Trials Innovation in the Division of Epidemiology, Department of Biostatistics, Epidemiology, and Informatics, in collaboration with the Palliative and Advanced Illness Research Center, seeks candidates with a PhD in Statistical Epidemiology, Biostatistics, Statistics, or a closely related quantitative field, with 1+ years of postdoctoral experience. The ideal candidates will be outstanding early-career researchers who will advance innovative clinical trial methodologies and lead cutting-edge research in the statistical design, analysis, monitoring, and interpretation of complex multi-arm, cluster, pragmatic, Bayesian, adaptive, and platform randomized trials. These faculty will be expected to lead and publish high-impact research in top-tier biostatistics, clinical trial, and clinical research journals; support, prepare, and submit grant applications; and support ongoing randomized trials and trial methodology awards with Penn faculty and external partners. In these roles, they will serve as lead biostatisticians on multi-center randomized clinical trials and methodology projects and grants, develop and evaluate composite outcome measures and interpretation frameworks, apply causal inference methods to augment experimental data interpretation, and provide independent statistical expertise and leadership to research teams.
The Department of Biostatistics and Epidemiology at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for several Assistant Professor positions in the non-tenure research track. Expertise is required in the specific area of the statistical design and analysis of randomized clinical trials. Applicants must have a Ph.D. or equivalent degree.
Additional qualifications include:
• A strong background and expertise in Bayesian statistical methods, causal inference, machine learning, pragmatic trial designs with cluster-randomization methods, and complex missing data methodology.
• Expertise in statistical programming (R, Python, Stan/BUGS).
• Proficiency with clinical trial simulation to support both methodological research and the initial design and subsequent modification of trials.
• Experience supporting large-scale trials, clinical research networks, and/or data and safety monitoring board statistical activities.
• Experience collaborating with clinician-scientists, particularly physician-scientists.
• Proficiency in analyzing and interpreting patient-reported outcome measures such as quality-of-life endpoints, including handling of missing data such as that due to non-response, death, or other intercurrent events.
• Demonstrated aptitude working with state-of-the-art computing infrastructure, Overleaf/LaTeX, GitHub, and supporting reproducible research pipelines.
Research or scholarship responsibilities may include demonstrated ability to lead peer-reviewed publications in clinical trials methodology and support multi-site collaborative research projects.
The Center for Clinical Trials Innovation in the Division of Epidemiology, Department of Biostatistics, Epidemiology, and Informatics, in collaboration with the Palliative and Advanced Illness Research Center, seeks candidates with a PhD in Statistical Epidemiology, Biostatistics, Statistics, or a closely related quantitative field, with 1+ years of postdoctoral experience. The ideal candidates will be outstanding early-career researchers who will advance innovative clinical trial methodologies and lead cutting-edge research in the statistical design, analysis, monitoring, and interpretation of complex multi-arm, cluster, pragmatic, Bayesian, adaptive, and platform randomized trials. These faculty will be expected to lead and publish high-impact research in top-tier biostatistics, clinical trial, and clinical research journals; support, prepare, and submit grant applications; and support ongoing randomized trials and trial methodology awards with Penn faculty and external partners. In these roles, they will serve as lead biostatisticians on multi-center randomized clinical trials and methodology projects and grants, develop and evaluate composite outcome measures and interpretation frameworks, apply causal inference methods to augment experimental data interpretation, and provide independent statistical expertise and leadership to research teams.
What University Of Pennsylvania employees say
Pay
Benefits
Hours and flexibility
Workplace
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About University of Pennsylvania
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The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn's distinctive interdisciplinary approach to scholarship and learning. As an employer Penn has been ranked nationally on many occasions with the most recent award from Forbes who named Penn one of America's Best Employers By State in 2021.
Industry
Colleges, universities, and professional schools
Company size
10,000+ Employees
Headquarters location
Philadelphia, PA, US
Year founded
1740