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Overnight Computer Science Postdoc information

What are the key skills and qualifications needed to thrive as an Overnight Computer Science Postdoc, and why are they important?

To thrive as an Overnight Computer Science Postdoc, you need a PhD in computer science or a related field, strong research skills, and expertise in your chosen area of study. Experience with programming languages (such as Python, Java, or C++), data analysis tools, and version control systems like Git is critical, along with familiarity with relevant computational frameworks. Excellent problem-solving abilities, self-motivation, and strong written and verbal communication skills help you excel in independent and collaborative research, especially during non-standard hours. These competencies enable you to contribute original findings, manage complex projects, and effectively communicate results within the academic community.

What are the typical challenges faced by an Overnight Computer Science Postdoc and how can they be managed effectively?

An Overnight Computer Science Postdoc often faces the challenge of maintaining productivity and focus during non-traditional working hours, which can impact work-life balance and collaboration with daytime colleagues. Managing these challenges involves establishing a structured routine, utilizing collaboration tools to stay connected with team members, and setting clear communication expectations. Additionally, it's important to prioritize self-care and leverage flexible scheduling when possible to maintain overall well-being and research effectiveness.

What is an Overnight Computer Science Postdoc?

An Overnight Computer Science Postdoc is a postdoctoral researcher in computer science who primarily works during nighttime hours. These positions typically involve conducting advanced research, collaborating on academic papers, and contributing to ongoing projects in areas like artificial intelligence, machine learning, or cybersecurity. Working overnight may be required to align with global research teams, utilize available computing resources, or accommodate personal schedules. Applicants generally need a recent Ph.D. in computer science or a closely related field. The role helps postdoctoral researchers gain further experience and prepare for faculty or industry positions.

What is the difference between Overnight Computer Science Postdoc vs Research Scientist?

AspectOvernight Computer Science PostdocResearch Scientist
CredentialsPhD in Computer Science or related fieldMaster's or PhD, often with specialized expertise
Work EnvironmentAcademic or research institution, often with flexible hoursIndustry labs or corporate R&D, standard working hours
Employer & IndustryUniversities, research institutesTech companies, R&D divisions
Search & Comparison IntentUnderstanding academic vs industry roles, work hours, credentialsCareer transition, industry-specific roles

The Overnight Computer Science Postdoc typically involves academic research with flexible hours and a focus on advancing knowledge in computer science. In contrast, a Research Scientist usually works in industry, with standard hours and applied research goals. Both roles require advanced degrees, but their work environments and career paths differ significantly.

What are the most commonly searched types of Computer Science Postdoc jobs in Chicago, IL? The most popular types of Computer Science Postdoc jobs in Chicago, IL are:
Overnight Computer Science Postdoc jobs near you
Postdoctoral Appointee - Scientific Machine Learning for Surrogate Modeling and Power Grid Dynamics

Postdoctoral Appointee - Scientific Machine Learning for Surrogate Modeling and Power Grid Dynamics

Argonne National Laboratory

Lemont, IL • On-site

$70.76K - $117.93K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

The Mathematics and Computer Science Division (MCS) at Argonne National Laboratory is seeking a Postdoctoral Appointee to conduct cutting-edge research in scientific machine learning, focusing specifically on developing machine learning-based surrogates and emulators for the dynamics of power grids. This role involves creating advanced probabilistic models that capture the complex behaviors of dynamical systems, which will be integrated into large-scale optimization frameworks to enhance the efficiency and reliability of power grid operations.

The Postdoctoral Appointee will be responsible for the conceptual framework, design, and implementation of these machine learning models, ensuring trustworthy computations and scalability on the DOE's leadership computing facilities. The focus will be on developing robust, scalable solutions that are computationally efficient and maintain accuracy within the operational constraints of real-world power systems.

Position Requirements

Required Skills and Qualifications:

  • Ph.D. (completed within the past 0-5 years) in computer science, electrical engineering, applied mathematics, or a related field.

  • Strong proficiency in Python, with additional experience in C, C++, or similar languages.

  • Demonstrated expertise in machine learning, especially in the context of dynamical systems modeled by differential-algebraic equations.

  • Experience with high-performance computing and the ability to scale models using distributed computing environments.

  • Excellent oral and written communication skills for effective collaboration across multiple teams.

  • Commitment to embodying the core values of impact, safety, respect, and teamwork in all endeavors.

Preferred Skills and Qualifications:

  • Extensive experience with power grid models and large-scale optimization problems.

  • Familiarity with developing machine learning surrogates and emulators for dynamical systems.

  • Proficiency in managing large datasets and training with GPU-enabled computing resources.

  • Expertise in numerical optimization and familiarity with ML frameworks such as PyTorch, Jax, or TensorFlow.

  • A strong foundation in statistical methods, probability theory, or uncertainty quantification is highly advantageous.

Job Family

Postdoctoral

Job Profile

Postdoctoral Appointee

Worker Type

Long-Term (Fixed Term)

Time Type

Full timeThe expected hiring range for this position is $70,758.00-$117,925.00.

Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.

Click here to view Argonne employee benefits!

As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.

Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.

All Argonne offers of employment are contingent upon a background check that includes an assessment of criminal conviction history conducted on an individualized and case-by-case basis. Please be advised that Argonne positions require upon hire (or may require in the future) for the individual be to obtain a government access authorization that involves additional background check requirements. Failure to obtain or maintain such government access authorization could result in the withdrawal of a job offer or future termination of employment.

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