ZipRecruiter

Log In

1

Physics Informed Machine Learning Jobs in Manchester, NH

previous page

Showing results 21-28

All JobsPhysics Informed Machine Learning JobsPhysics Informed Machine Learning Jobs in Manchester, NH

Physics Informed Machine Learning information

See Manchester, NH salary details

$5

$19

$25

How much do physics informed machine learning jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for physics informed machine learning in Manchester, NH is $19.98, according to ZipRecruiter salary data. Most workers in this role earn between $12.45 and $25.38 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What job categories do people searching Physics Informed Machine Learning jobs in Manchester, NH look for?

The top searched job categories for Physics Informed Machine Learning jobs in Manchester, NH are:

Physics Informed Machine Learning jobs near you

Medical Assistant

SALEM NEW HAMPSHIRE PHYSICIANS PC

North Andover, MA • On-site

$25/hr

Full-time

Medical

Re-posted 16 days ago

Job description

Position: Medical Assistant (Experienced)
Type: Temporary / Seasonal Coverage (Holidays) with strong potential to become permanent
Schedule: Full-time, with potential transition into a permanent 24-hour position (details discussed in interview)
Start Date: Immediate
Sign-On Bonus: Yes (details provided during hiring process)
Overview
We are seeking a Medical Assistant to join our team! This is an immediate, temporary position to help cover the holiday schedule and support our transition to a new EMR system. The right candidate may be offered a permanent role following the temporary period.
As a Medical Assistant, you will be preparing for each patient visit by preparing charts and pulling notes before their arrival, providing routine support alongside nurses and medical staff, and assisting with keeping track of tests and lab reporting to ensure everything arrives on time and the patient is kept informed on their condition and care. You will also be helping manage the inventory of medical supplies, setting up machines and testing equipment, and cleaning instruments and rooms as needed.
Key Responsibilities
  • Room patients and assist providers during clinic visits
  • Perform vitals, patient intake, and accurate documentation
  • Prepare charts and pull patient notes prior to visits
  • Provide routine clinical support alongside nurses and medical staff
  • Track tests, lab reporting, and ensure timely follow-up with patients
  • Handle patient call-backs with lab/test results and provider instructions
  • Manage medication refill requests efficiently and safely
  • Support day-to-day clinic flow and patient coordination
  • Assist staff during EMR transition and adapt to updated workflows
  • Maintain inventory of medical supplies
  • Set up machines/testing equipment and clean instruments/rooms as needed
  • Maintain professionalism, patient confidentiality, and excellent customer service
Required Qualifications
  • Medical Assistant experience is required (no entry-level applicants for this role)
  • Proven experience rooming patients in a busy clinical setting
  • Strong background with medication refills and result follow-ups
  • Must have working knowledge of eClinicalWorks (eCW)

  • Comfortable learning and supporting a transition to a new EMR system
  • Excellent communication and organizational skills
  • Reliable, flexible, and able to start immediately
Ideal Candidate
  • Strong customer service and patient-facing skills
  • Interest in working in a fast-paced medical environment
  • Previous medical office experience
  • Highly organized, dependable, and team-oriented
Why Join Us
  • Sign-on bonus available

  • Immediate start with consistent hours through the holidays
  • Opportunity to transition into a long-term permanent role
  • Supportive clinical environment during a major systems upgrade