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Data Science Phd Jobs in Rochester, NY (NOW HIRING)

Sapsol Technologies Inc

Medical Engineer

Rochester, NY · On-site

Contribute to related data processing and image reconstruction workflows when required. B) Image ... Master's or PhD in MRI Physics, Biomedical Engineering, Medical Physics, Electrical Engineering ...

University of Rochester

Neonatologist

Rochester, NY · On-site

The division's clinical research group includes research coordinators, research nurses, and data ... Science (NCATS)-funded Clinical and Translational Sciences Institute (CTSI). The CTSI provides ...

IMC Inc

Machine Learning Research Lead

Farmington, NY

$250K - $300K/yr

Oversee data acquisition, preprocessing, and feature engineering for structured and unstructured ... PhD or Master's in Engineering, Math, Statistics, Computer Science, or related quantitative field ...

Fermilab

Quantum Computing Engineer I

Batavia, NY

$79.30K - $104.40K/yr

Writing scientific papers, technical documents, and engineering notes. * Performing other duties as ... PhD in Electronics Engineering or Physics (post-degree experience a plus). Applicable Knowledge ...

University of Rochester

Sr Electrical Engineer

Rochester, NY · On-site

$86.48K - $129.72K/yr

... data, education, experience, qualifications, expertise of the individual, and internal equity ... The candidate will be working independently with scientists and engineers from other disciplines in ...

University of Rochester

Neonatologist

Rochester, NY

$230K - $250K/yr

The division's clinical research group includes research coordinators, research nurses, and data ... Science (NCATS)-funded Clinical and Translational Sciences Institute (CTSI). The CTSI provides ...

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What are the key skills and qualifications needed to thrive as a Data Science PhD, and why are they important?

To thrive as a Data Science PhD, you need advanced expertise in statistics, machine learning, data analysis, and a doctoral degree in a quantitative field. Proficiency in programming languages like Python or R, experience with big data frameworks (e.g., Spark, Hadoop), and familiarity with data visualization tools are typically required. Critical thinking, problem-solving, and strong communication skills help you translate complex data insights for diverse stakeholders. These skills are vital for driving innovative research, making data-driven decisions, and contributing impactful solutions in data-centric environments.

What are some common challenges faced by Data Science PhDs when transitioning from academia to industry roles?

Data Science PhDs often encounter challenges such as adapting to the faster pace and collaborative nature of industry projects compared to academic research. In industry, there is a greater emphasis on delivering practical solutions within tight deadlines and working closely with cross-functional teams like engineering and product management. Additionally, data science work in industry may require balancing technical rigor with business impact, often prioritizing actionable insights over exhaustive analysis. Building strong communication and stakeholder management skills can help ease this transition.

What is a Data Science PhD?

A Data Science PhD is a doctoral-level degree focused on advanced research in data science, which combines elements of statistics, computer science, and domain expertise. Students in a Data Science PhD program typically work on developing new methods for analyzing large datasets, creating machine learning algorithms, and addressing complex problems in areas such as artificial intelligence, data mining, and predictive analytics. Graduates are prepared for careers in academia, research, and industry, where they can lead data-driven projects and contribute to advancements in the field.
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Infographic showing various Data Science Phd job openings in Rochester, NY as of May 2026, with employment types broken down into 92% Full Time, 6% Part Time, and 2% Contract. Highlights an 95% Physical, 3% Hybrid, and 2% Remote job distribution.
Medical Engineer

Medical Engineer

SAPSOL Technologies Inc

Rochester, NY

Other

Posted yesterday

Job description

This role supports the development, integration, and validation of advanced MRI methods across two research workstreams:

  • Oscillating Gradient Diffusion (OGSE/OGD) in collaboration with Vanderbilt University, and
  • FLORET‑based UTE imaging (non‑Cartesian) in collaboration with Cincinnati Children’s Hospital.

The engineer will coordinate program execution while contributing technically to pulse sequence implementation, image reconstruction and software refinement, and data processing within the Philips MRI research environment. The emphasis is on program oversight, technical coordination, and collaborative execution, rather than independent subject‑matter leadership in diffusion MRI or FLORET.

Note: This role focuses on technical engagement and delivery. It does not include clinical trial operations or regulatory ownership.

Core Responsibilities

A) Technical Development – Pulse Sequence (OGSE/OGD)

  • Refine and extend existing OGSE pulse sequence code in the Philips research environment.
  • Implement additional features, improve robustness, and ensure correct sequence functionality.
  • Support deployment and on‑scanner integration on Philips MRI systems.
  • Contribute to related data processing and image reconstruction workflows when required.

B) Image Reconstruction & Software Development (FLORET / Non‑Cartesian)

  • Implement and validate non‑Cartesian MRI reconstruction pipelines (including those supporting FLORET UTE acquisitions).
  • Support software deployment and integration of reconstruction tools within Philips research systems.
  • Refine reconstruction workflows, add new features, and improve system interfaces and usability.
  • Perform data validation and quality checks; evaluate reconstruction stability and artifact behavior.

C) Experimental Collaboration & Validation

  • Coordinate experiment planning with Vanderbilt researchers, Cincinnati Children’s teams, and clinical MRI staff.
  • Support execution of scanner experiments as needed.
  • Assist with validation of OGSE and FLORET acquisition outputs through systematic testing and comparative analysis.
  • Prepare technical validation summaries/reports and ensure outputs align with program deliverables and milestones.
  • Document results, assumptions, and change histories with strong discipline.

Qualifications

Required

  • Strong familiarity with vendor‑specific MRI pulse sequence programming (preferably Philips research environments).
  • Solid foundations in MRI reconstruction, including non‑Cartesian methods, and software engineering.
  • Hands‑on experience with C++ / Python / MATLAB for algorithm and tooling development.
  • Ability to collaborate effectively across industry and academic partners; clear written and verbal communication.
  • Proven ability to operate under hardware constraints and in structured, sprint‑based execution models.

Preferred

  • Master’s or PhD in MRI Physics, Biomedical Engineering, Medical Physics, Electrical Engineering, Computer Science, or related field.
  • Experience with Philips MRI research environments (e.g., research interfaces, integration workflows).
  • Exposure to OGSE/OGD diffusion methods and/or FLORET UTE imaging (deep expertise not required).
  • Experience with MRI data processing, QA/QC, and validation workflows.

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