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Decision Making Postdoc information

What are common challenges faced by decision making postdocs in balancing independent research with collaborative projects?

Decision Making Postdocs often need to strike a balance between pursuing their own research interests and contributing to larger lab or team projects. Juggling independent work with collaborative studies can be challenging, especially when timelines or methodologies differ. Success in this role typically involves strong communication skills, flexibility, and effective time management, as well as openness to interdisciplinary feedback. Navigating these dynamics helps postdocs build valuable experience for future academic or industry positions.

What is a decision making postdoc?

A Decision Making Postdoc is a researcher who has completed their PhD and is conducting advanced research in the field of decision-making. This typically involves studying how individuals or groups make choices, using methods from psychology, neuroscience, economics, or related disciplines. Postdocs in this area often work on experimental design, data analysis, and publishing their findings, while collaborating with faculty and other researchers. The position is usually temporary, intended to further develop scholarly skills and prepare for an academic or industry career.

What is the difference between Decision Making Postdoc vs Data Scientist?

AspectDecision Making PostdocData Scientist
Required CredentialsPhD in relevant field, research experienceBachelor's or Master's in CS, stats, or related field; often a PhD preferred
Work EnvironmentAcademic or research institutions, labsTech companies, finance, healthcare, industry
Employer & Industry UsageResearch-focused roles, academiaIndustry roles, product development, analytics
Common Search & ComparisonDecision Making Postdoc vs Data Scientist

The Decision Making Postdoc primarily focuses on research and theoretical analysis related to decision processes, often within academic or research settings. In contrast, Data Scientists apply data analysis, modeling, and machine learning techniques to solve practical problems in industry. While both roles require strong analytical skills, Decision Making Postdocs emphasize research and theoretical frameworks, whereas Data Scientists focus on data-driven solutions for business applications.

What are the key skills and qualifications needed to thrive as a decision making postdoc, and why are they important?

To thrive as a Decision Making Postdoc, you need a PhD in psychology, neuroscience, economics, or a related field, along with a strong background in experimental design and data analysis. Expertise in statistical software (such as R, MATLAB, or Python) and experience with behavioral or neuroimaging methods are typically required. Outstanding analytical thinking, problem-solving abilities, and effective scientific communication skills help you excel in collaborative research environments. These competencies are crucial for producing rigorous research, advancing knowledge in decision-making science, and contributing to interdisciplinary projects.
What are popular job titles related to Decision Making Postdoc jobs in California? For Decision Making Postdoc jobs in California, the most frequently searched job titles are:
What job categories do people searching Decision Making Postdoc jobs in California look for? The top searched job categories for Decision Making Postdoc jobs in California are:
What cities in California are hiring for Decision Making Postdoc jobs? Cities in California with the most Decision Making Postdoc job openings:
Decision Making Postdoc jobs near you

Postdoctoral Scholar

Lawrence Berkeley National Laboratory

Berkeley, CA • On-site

Full-time

Medical, Retirement, PTO

Re-posted 26 days ago

Lawrence Berkeley National Laboratory rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

2nd of 120 rated laboratories

Job description

Berkeley Lab's Center for Advanced Mathematics for Energy Research Applications (CAMERA) has a new opening for a postdoctoral scholar to develop cutting-edge mathematics and algorithms to analyze complex data from Department of Energy (DOE) experimental facilities.
This role involves research and development spanning areas such as optimization, Fourier analysis, numerical linear algebra, statistics, machine learning, and high-performance computing for one or more of the following: (1) reconstruction of 3D+ structure, heterogeneity, and/or dynamics from scattering and/or microscopy data; (2) autonomous analysis and decision making for self-driving and/or human-in-the-loop experiments; (3) computer vision for extracting complex patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms leading to new applications of machine learning and artificial intelligence to analysis of experimental data. Of particular interest will be new approaches for tackling multimodal data, quantifying uncertainty, providing rigorous theoretical guarantees, and modelling complex physics, noise processes, and measurement error. You will work closely with mathematicians, software engineers, physicists, materials scientists, and beamline scientists to implement these new tools on HPC computer architectures and deliver them as user-friendly software to meet DOE experimental facility needs.
We're here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!
Why join Berkeley Lab?
We invest in our employees by offering a total rewards package you can count on:
  • Exceptional health and retirement benefits, including pension or 401K-style plans
  • A culture where you'll belong - we are invested in our teams!
  • In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year.
  • Parental bonding leave (for both mothers and fathers)

You will:
  • Conduct independent and collaborative research to develop new mathematics and algorithms for analyzing complex data from DOE experimental facilities.
  • Develop new mathematical algorithms targeting one or more focus areas: (1) 3D+ reconstruction of structure/heterogeneity/dynamics from scattering and/or microscopy data; (2) autonomous analysis and decision-making for self-driving and/or human-in-the-loop experiments; (3) computer vision for extracting patterns, structure, and meaning from images and/or volumes; and (4) new mathematics and algorithms that enable new reliable new applications of machine learning and artificial intelligence to experimental data analysis.
  • Make advances in one or more of: multimodal data fusion/joint inference; uncertainty quantification with realistic noise/measurement error; complex physics- and artifact-aware forward modeling; and theory-grounded guarantees for proposed algorithms.
  • Collaborate with scientific users and experimentalists at DOE experimental facilities to apply the developed software to real datasets and meet their scientific needs.
  • Publish results in peer-reviewed venues, present at conferences/workshops, and contribute to CAMERA's collaborative research activities.

We are looking for:
  • Ph.D. in Applied Mathematics, Computer Science, Physics, or related field.
  • Strong research track record developing advanced mathematical and computational methods for analyzing complex experimental or imaging data.
  • Demonstrated expertise in several of the following areas: inverse problems, statistics, optimization, uncertainty quantification, and/or computer vision/machine learning.
  • Strong foundation in at least one of: numerical linear algebra, Fourier/spectral methods, scientific computing, and/or high-performance computing.
  • Proven ability to publish in peer-reviewed venues and present research at seminars, workshops, and scientific conferences.
  • Excellent written and verbal communication skills, with the ability to contribute effectively to large, collaborative, multidisciplinary projects in a diverse environment.

Desired skills/knowledge:
  • Familiarity with modern machine learning methods and software, including experience applying them to scientific or experimental datasets.
  • Experience collaborating with domain scientists to analyze real experimental data and translate scientific questions into robust, actionable computational approaches.

Additional information:
  • Applications will be accepted until the job posting is removed.
  • Appointment type: This is a full-time, 2 year, postdoctoral appointment with the possibility of renewal based upon satisfactory job performance, continuing availability of funds and ongoing operational needs. You must have less than 3 years of paid postdoctoral experience. Salary for Postdoctoral positions depends on years of experience post-degree.
  • Salary range: The salary range for this position is $8,570 - $9,935 and is expected to start at $8,570 or above. Postdoctoral positions are paid on a step schedule per union contract and salaries will be predetermined based on postdoctoral step rates. Each step represents one full year of completed post-Ph.D. postdoctoral experience.
  • Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
  • Work modality: Work may be performed on-site, hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States.
  • Union Represented: This position is represented by a union for collective bargaining purposes.

Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov
Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.
Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.

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