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Image scientist skills for your resume and career

Updated January 8, 2025
4 min read
Quoted expert
Josh Kaplan Ph.D.
Below we've compiled a list of the most critical image scientist skills. We ranked the top skills for image scientists based on the percentage of resumes they appeared on. For example, 14.1% of image scientist resumes contained image processing as a skill. Continue reading to find out what skills an image scientist needs to be successful in the workplace.

15 image scientist skills for your resume and career

1. Image Processing

Here's how image scientists use image processing:
  • Researched emerging image processing techniques in order guarantee customer was on the leading edge of imagery analysis and exploitation.
  • Performed market research and performance analysis for auto-enhance image processing algorithms.

2. MATLAB

Here's how image scientists use matlab:
  • Developed, tested, and verified custom software tools written in Matlab, IDL, and C/C++ for scientific computation.
  • Programmed in C/C++, Basic, Matlab and a variety of scripting languages in both Windows and Unix.

3. Machine Learning

Here's how image scientists use machine learning:
  • Designed EMA using text mining and machine learning to parse and extract obesity biomarker from online databases.

4. PET

Here's how image scientists use pet:
  • Retained as consultant for cardiac MRI (CMRI) and PET study projects.
  • Develop individualized research plans structured around client projects Business expansion-Implemented a Bio-distribution program with optical, PET and SPECT imaging.

5. Data Analysis

Here's how image scientists use data analysis:
  • Manage high-volume data analysis, intelligence production, quality assurance, and delivery process.
  • Provide educated decision advisory according to scientific and clinical data analysis.

6. Remote Sensing

Here's how image scientists use remote sensing:
  • Collected and analyzed data derived from ground experiments for validation and verification of exploitation algorithms and calibration of remote sensing platforms.
  • Developed image chain for detection of hard targets using remote sensing.

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7. LiDAR

Here's how image scientists use lidar:
  • Investigated novel algorithms and disseminated new training material on standard practices for Lidar processing.
  • Researched and developed prototype test of rock strength with the usage of a point cloud generated from ground based Lidar system.

8. Image Quality

Image quality can indicate to the level of precision in which various imaging systems process, capture, compress, store, display and transmit the signals form an image. Image quality may have different meanings depending on the focus area that is being referred to.

Here's how image scientists use image quality:
  • Assess image quality impacts associated with collection, processing, dissemination, archival, exploitation and display of digital imagery.
  • Led the development of a scanner-based automatic image capture and image quality analysis system.

9. SAR

SAR is a measure of the rate of radiofrequency energy is absorbed per unit mass by a human body from the source being measured. This provides a simple way of measuring the RF exposure of cell phones to confirm if they are within the safety regulations set by the FCC. SSAR is averaged either over the entire body, or a little sample volume that is 1 g/10 g of tissue.

Here's how image scientists use sar:
  • Consult on sensor fusion and IOC details of an airborne multi-sensor integration project (HS, SAR, etc.).

10. Software Development

Software development is the mechanism by which programmers create computer programs. The Software Development Life Cycle (SDLC) is a framework for developing applications that follow technological needs and consumer requirements. It consists of many stages. The SDLC establishes an international standard that software developers can use to enhance and create their programs. It provides a well-defined framework for software developers to pursue in the production, maintenance, and design of premium quality software. The aim of the software development process is to create high-quality software on time and within budget.

Here's how image scientists use software development:
  • Lead the software development of a spectral imaging simulation tool.
  • Conducted software engineering methods research including real-time software development techniques and tools for analysis and design.

11. Product Quality

Product quality is the basic element of a business. It means to add features in a product or service in such a way that it meets the needs and wants of the customers. Enhancing the product quality also means improve the goods from any existing defects to ensure customer satisfaction.

Here's how image scientists use product quality:
  • Designed writer artifact quantification and automatic correction algorithms for NexPress digital printing system using Independent Component Analysis for improved product quality.
  • Followed QA and regulatory procedures for the design/development/testing and delivered product quality code of FDA-cleared medical device.

12. AGI

Here's how image scientists use agi:
  • Performed duties as the Data Manager and Senior AGI Analyst.

13. C

Here's how image scientists use c:
  • Developed software under Unix and Macintosh in C and C++.
  • Designed and developed an advanced reporting system written in C and C++ with Oracle database backend using oci.

14. C++

C++ is a general-purpose programming language that is used to create high-performing applications. It was invented as an extension to the C language. C++ lets the programmer have a high level of domination over memory and system resources. C++ is an object-oriented language that helps you implement real-time issues based on different data functions

Here's how image scientists use c++:
  • Advanced graphical C++ software for visualization and exploitation of 3D models, imagery and vector layers.
  • Coded C++ application that batch converts file formats from MEDM to EDM (GUI display editors).

15. Algorithm Development

Here's how image scientists use algorithm development:
  • Collaborated on Multi-INT IR&D, providing algorithm development and verification expertise.
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What skills help Image Scientists find jobs?

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Josh Kaplan Ph.D.Josh Kaplan Ph.D. LinkedIn profile

Associate Professor, Western Washington University

Demonstrating a skill set that is unique, such as experience with a rare technical research approach, or demonstrating that you can save your employer money by utilizing free resources, can be used to negotiate a higher salary.
Do you want to know more?
Read more about what experts have to say about image scientist

List of image scientist skills to add to your resume

Image scientist skills

The most important skills for an image scientist resume and required skills for an image scientist to have include:

  • Image Processing
  • MATLAB
  • Machine Learning
  • PET
  • Data Analysis
  • Remote Sensing
  • LiDAR
  • Image Quality
  • SAR
  • Software Development
  • Product Quality
  • AGI
  • C
  • C++
  • Algorithm Development
  • DOD
  • Data Collection
  • NGA
  • Clinical Trials
  • MR
  • Visualization
  • Biomarkers
  • Research Projects
  • Prototyping
  • Linux
  • Extraction
  • Technical Support
  • Software Tools
  • R
  • Adaptive
  • Color Science
  • Statistical Analysis
  • FDA
  • RF
  • Color Correction
  • Digital Pathology

Updated January 8, 2025

Zippia Research Team
Zippia Team

Editorial Staff

The Zippia Research Team has spent countless hours reviewing resumes, job postings, and government data to determine what goes into getting a job in each phase of life. Professional writers and data scientists comprise the Zippia Research Team.

Updated January 8, 2025

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