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Remarkable increase in peak power-density values coupled with the hotspot migration caused by workload variance motivates the need for multiple thermal monitoring circuits distributed across the die. The effect of intra-die process-variations on deep sub-micron circuits is significant enough to undermine their robustness. Accordingly, there is change in the response of thermal sensors occupying different process-corners which causes a shift in their calibration-constants. To save on tester cost, modern microprocessors employ a single, 2-point hard calibration model (slope-intercept form). In a multi-sensor environment, a single calibration equation will be rendered ineffective due to sparse sensor distribution that will be afflicted by varying degrees of process-variation. Thus, our aim is to estimate the process-induced drift in the calibration-constants of the thermal sensors. To this end, we propose a novel, supply and temperature independent, process-sensor which offers a high sensitivity of 3.35%/5 mV variation in Vth and a low power consumption of 4-25 nW. The process-estimates obtained are plugged into an analytical model used to describe the process-dependence of a ring-oscillator based thermal sensor and generate the process-shifted calibration constants. HSPICE simulations in 45 nm indicate that in the presence of process-variations having 3-Â¿ variability of +/-15% in all process-parameters, the average measurement error of a ring-oscillator-based thermal sensor with process-corrected calibration constants is reduced by >3X for slope and >10X for intercept as compared to one with static constants.