2

Remote Signal Processing Postdoctoral Jobs in Oregon

Machine Learning Engineer

Foster, OR · On-site +1

$160K - $215K/yr

Possibility for Remote. Key Responsibilities: * Design, develop, and optimize advanced algorithms ... Develop signal-processing and image-analysis algorithms using classical methods as well as modern ...

New

$99.61K - $136.96K/yr

Hybrid (+50% Remote) - Remote 60% / Onsite 40% EXPECTED PAY RANGE: Data Scientist I: $99,608 - $136 ... Signal processing or physics-based modeling * Graph-based reasoning or causal inference * Full ...

Lead assay development optimization and R&D process acceleration using advanced statistical and ML ... or postdoctoral research experience in MedTech, diagnostics, biopharma, or applied AI domains.

Upsunners are a remote, global workforce, and we thrive in a multicultural team. We are committed ... Knowledge Transfer: As the product matures, hand off processes and assets to the broader ...

Founded in 2008, OSV is the leading exclusive provider of Business-Process-as-a-Service (BPaaS ... This role sits at the intersection of product, data, and go-to-market, translating signals and ...

next page

Showing results 1-20

Remote Signal Processing Postdoctoral information

What are the key skills and qualifications needed to thrive as a Remote Signal Processing Postdoctoral Researcher, and why are they important?

To thrive as a Remote Signal Processing Postdoctoral Researcher, you need a Ph.D. in electrical engineering, computer science, or a related field, with expertise in signal processing theory and algorithms. Experience with programming languages such as Python or MATLAB, and familiarity with simulation tools or machine learning frameworks, is typically required. Strong analytical thinking, independent research skills, and effective written and verbal communication set outstanding candidates apart. These skills are crucial for advancing research, publishing results, and collaborating remotely with interdisciplinary teams.

What are some common challenges faced by remote signal processing postdoctoral researchers, and how can these be effectively managed?

Remote signal processing postdocs often encounter challenges such as limited access to specialized lab equipment, potential communication barriers with collaborators, and the need for strong self-motivation and time management. To address these, many researchers leverage cloud-based computing resources, regularly schedule virtual meetings, and participate in collaborative online platforms to stay connected with their teams. Setting clear research goals and maintaining open communication with supervisors can also help ensure ongoing progress and support while working remotely.

What is a Remote Signal Processing Postdoctoral researcher?

A Remote Signal Processing Postdoctoral researcher is a scientist who has recently completed their Ph.D. and conducts advanced research in signal processing—analyzing and interpreting signals such as audio, images, or sensor data—while working remotely. This position typically involves developing new algorithms, analyzing data, and publishing results in scientific journals. The 'remote' aspect means that the researcher can work from anywhere, collaborating with teams and contributing to projects online. These roles are common in fields like telecommunications, biomedical engineering, and geosciences.
What are the most commonly searched types of Signal Processing Postdoctoral jobs in Oregon? The most popular types of Signal Processing Postdoctoral jobs in Oregon are:
What are popular job titles related to Remote Signal Processing Postdoctoral jobs in Oregon? For Remote Signal Processing Postdoctoral jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Remote Signal Processing Postdoctoral jobs in Oregon look for? The top searched job categories for Remote Signal Processing Postdoctoral jobs in Oregon are:
What cities in Oregon are hiring for Remote Signal Processing Postdoctoral jobs? Cities in Oregon with the most Remote Signal Processing Postdoctoral job openings:
Machine Learning Engineer

Machine Learning Engineer

Cellanome

Foster, OR • On-site, Remote

$160K - $215K/yr

Other

Posted 2 days ago


Job description

The Machine Learning Engineer will work in close collaboration with the core instrument, assay and software teams to develop algorithms for data analysis and workflow automation. This role reports to the Sr. Director AI and can be based in our San Diego CA or Foster City CA offices. Possibility for Remote.

Key Responsibilities:

  • Design, develop, and optimize advanced algorithms for workflow automation, which include computer vision and computational geometry components.
  • Develop signal-processing and image-analysis algorithms using classical methods as well as modern AI/ML approaches, including neural networks.
  • Perform system-level analysis, simulation, and validation to ensure algorithm performance meets product requirements.
  • Collaborate with cross-functional hardware, software, and product engineering teams to integrate algorithms into our broader software ecosystem.
  • Optimize algorithms for deployment on edge devices, GPUs, and high-performance computing environments with considerations for latency, throughput, and memory efficiency.
  • Create technical documentation, validation reports, and performance metrics to support product development and cross-team collaboration.

Role Requirements:

  • Typically requires a Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field with 5+ years of relevant experience, or a Master's degree with 3+ years of relevant experience.
  • Experience developing, implementing, and validating algorithms for optimization, automation, sensing, data analysis, or image-processing applications.
  • Strong programming skills in Python with experience developing production-quality, maintainable, and well-documented code.
  • Solid understanding of software development fundamentals, including debugging, version control, testing, and code optimization.
  • Familiarity with AI/ML concepts and workflows, including data preprocessing, model training, evaluation, and deployment.
  • Experience with image analysis, computer vision, signal processing, or data-driven algorithm development.
  • Understanding of mathematical foundations relevant to algorithm development, including linear algebra, probability/statistics, optimization methods, and estimation theory.
  • Experience applying algorithmic techniques such as optimization, dynamic programming, numerical methods, or statistical modeling to solve engineering problems.
  • Familiarity with workflow automation, process optimization, or development of efficient data-processing pipelines.
  • Ability to analyze complex technical problems, evaluate tradeoffs, and develop scalable algorithmic solutions.
  • Excellent communication skills and ability to work independently and collaboratively in a multidisciplinary team environment.

Preferred Qualifications:

  • Proficiency in C++, C#, or other high-performance programming languages for algorithm deployment and system integration.
  • Experience developing AI/ML algorithms for image analysis, pattern recognition, anomaly detection, or automated decision systems.
  • Advanced familiarity with modern computer vision and deep learning architectures, including Vision Transformers (ViTs), CNNs, object detection, segmentation, or multimodal AI models.
  • Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar platforms.
  • Experience optimizing algorithms for performance, scalability, memory efficiency, or real-time execution.
  • Familiarity with optimization and estimation techniques such as convex optimization, Kalman filtering, Bayesian estimation, nonlinear optimization, or stochastic methods.

We  provide competitive total compensation packages, including base pay, benefits, and equity. In California, the estimated base salary range for this position is $160,000 - $215,000/year. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.